university microfilms international...university of hawaii, ph.d., 1977 psychology, social 77......

INFORMATION TO USERS

This material was produced from a microfilm copy of the original document. Whilethe most advanced technological means to photograph and reproduce this documenthave been used, the quality is heavily dependent upon the quality of the originalsubmitted.

The following explanation of techniques is provided to help you understandmarkings or patterns which may appear on this reproduction.

1. The sign or "target" for pages apparently lacking from the documentphotographed is "Missing Page(s)". If it was possible to obtain the missingpage(s) or section, they are spliced into the film along with adjacent pages.This may have necessitated cutting thru an imageand duplicating adjacentpages to insure you complete continuity.

2. When an image on the film is obliterated with a large round black mark, itis an indication that the photographer suspected that the copy may havemoved during exposure and thus cause a blurred image. You will find .agood imageof the page in the adjacent frame.

3. When a map, drawing or chart, ete., was part of the material beingphotographed the photographer followed a definite method in"sectioning" the material. It is customary to begin photoing at the upperleft hand corner of a large sheet and to continue photoing 'from left toright in equal sections with a small overlap. If necessary, sectioning iscontinued again - beginning below the first row and continuing on untilcomplete.

4. The majority of users indicate that the textual content is of greatest value,however, a somewhat higher quality reproduction could be made from"photographs" if essential to the understanding of the dissertation. Silverprints of "photographs" may be ordered at additional charge by writingthe Order Department, giving the catalog number, title, author andspecific pages you wish reproduced.

5. PLEASE NOTE: Soma pages may have indistinct print. Filmed asreceived.

University Microfilms International300 North Zeeb RoadAnn Arbor, Michigan 48106 USA

St. John's Road, Tyler's GreenHigh Wycombe, Bucks, England HP10 8HR

University of Hawaii,Ph.D., 1977Psychology, social

77... 23,500

WILSON, Kenneth Wayne, 1946"ENVIRONMENTAL RELATIONS TO COGNITIVEABILITIES ACROSS THREE ETHNIC GROUPS.

"

j

Ilfi~,.If Xerox University Microfilms, Ann Arbor, Michigan 48106tt.-

ENVIRONMENTAL RELATIONS TO COGNITIVE ABILITIES

ACROSS THREE ETHNIC GROUPS

A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THEUNIVERSITY OF HAWAI I IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

IN PSYCHOLOGY

MAY 1977

By

Kenneth W. Wilson

Dissertation Committee:

Ronald C. Johnson, ChairmanRobert E. Cole

Gerald McClearnErnst S. Reese

Steven G. VandenbergHerbert Weaver

ACKNOWLEDGEMENTS

This research was conducted with the use of funds from

grant HD06669, awarded by the National Institute of Child

Health and Human Development to a group of,co-prlncipal

Investigators (G. C. Ashton, R. C. Johnson, M. P. Mi, and M.

N. Rashad at the University of Hawaii, and J. C. DeFries, G.

E. McClearn, S. G. Vandenberg, and J. R. Wilson at the

University of Colorado). The writer expresses his gratitude

to these co-principal investigators, and extends his

appreciation to the staff of the Behavioral Biology

Laboratory, University of Hawaii.

iii

Environmental reatlonshlps to cognitive abilities acrossthree ethnic groups

Abstract

Using data on 1745 offspring from families In Hawaii andKorea, dimensions factored from environmental variables(broad definition, Including genetic Influences) areexamined and related to cognitive abilities by means ofmultiple regression.

Three ethnic groups were represented: Americans ofEuropean Ancestry (AEA'S, N=1122)i Americans of JapaneseAncestry (AJA's, N=380); and native Koreans (N=243).Cognitive abilities are defined by factoring 15 tests intofour factors: verbal, spatial, perceptual speed, and memory(DeFries, 1974). Also included was the first principalcomponent (Spearman's 'gil from a previous analysis.

Common factor analysis was used to factor environmentalmeasures from each ethnic group Into 16 oblique dimensions.Coefficients of congruence show high similarities acrossgroups for approximately three-quarters of the factors.Factors unique to each group are discussed.

Second order structures show soclo-economic status,parental and self ratings, family size, and family age to beImportant cross-cultural areas of influence.

Multiple correlations showed the total environment to berelated most strongly to Spearman's 'g' followed by verbalability, perceptual speed, spatial ability, and memory.Cross-cultural factors important to verbal abil ity wereschool work, amount of reading, and socio-economic status.Spatial ability was related to the subject's perception oftheir mathematical ability, and perceptual speed related todevelopmental and pregnancy problems. Spearman's 'g' showeddiverse relationships across groups, but again school work,reading, and soclo-economic status showed influence.

In order to conceptual ize patterns of relationshipsbetween environmental variables and cognitive abll ities,simple (Pearson) environment-ability correlations were rankordered for each ethnic-abil tty combination. These 15patterns of correlations were then compared by means ofSpearman's rank correlation (rho).

The rho's were higher for pairwise comparisons within anethnic group across abilities than for comparisons ofsimilar abilities across ethnic groups. Comparisons acrossabilities, notably verbal, Spearman's 'g', spatial, andperceptual speed showed significant (p<.01) correlations,but these were generally lower than within ethnic groupcomparisons.

In summary, highly congruent factors related to cognitiveabilities across cultural groups in similar ways.

iv

TABLE OF CONTENTSPage

ACKNOWLEDGEMENTS ••••• •••• • •••• iii

ABSTRACT •••••••••• •• • • • • • • •• iv

LIST OF TABLES ••••• •••••• • • • • •• vi

LIST OF ABBREVIATIONS •••• ••• • • • • • ix

CHAPTER REVIEW OF LITERATURE •••••• •• 1

CHAPTER II METHOD •••••• •• • • • • • •• 39

CHAPTER III RESULTS • • • • • •• • • • • • • •• 60

CHAPTER IV DISCUSSION ••••••••• • • •• 116

BIBLIOGRAPHY •••••••••••••• •••• 147

. v

LI ST OF TABLES

TABLE

Page1 INTERRELATIONSHIPS BETWEEN MENTAL ABILITIES AND

ENVIRONMENTAL FACTORS CMARJORIBANKS, 1972) ••• 30

2 STEPWISE MULTIPLE REGRESSION - ENVIRONMENTALVARIABLES ON ACADEMIC CRITERIA CHILTON &MYER, 1966) • • • • • • • • • • • • • • •• 31

. . .

. . . . . .

. . . . . .

. . . . . . . .49

51

51

40

42

. .

FACTOR LOADINGS FOR FOUR COGNITIVE ABILITIESCBBL SAMPLE) •••••••••• • ••

KOREAN COGNITIVE FACTOR LOADINGS

MEAN AGE FOR EACH SUBJECT GROUP •

EXPLANATION OF EQ VARIABLE NAMES

CONGRUENCY COEFFICIENTS FOR COGNITIVE FACTORS

6

7

3

4

5

8 FACTOR STURCTURE OF OFFSPRING'S ATTITUDE SCORESAEAs • • • • • • • • • • • • • • • • • • • • •• 53

9 FACTOR STRUCTURE OF PARENTS' ATTITUDE SCORES-AEAs 53

10 FACTOR STRUCTURE OF OFFSPRINGS' ATTITUDE SCORESAJAs ••• • • • • • • • • • • • • • • • • • •• 54

11 FACTOR STRUCTURE OF PARENTS' ATTITUDE SCORES-AJAs 54

12 FACTOR STRUCTURE OF OFFSPRINGS' ATTITUDE SCORESKOREANS •••••••••••••••••• 55

13 FACTOR STRUCTURE OF PARENTS' ATTITUDE SCORESKOREANS • • • • • • • • • • • • • • • • •• 55

14 COMMUNALITIES AND EIGENVALUES FOR THE AEA EQSTRUCTURE ••••••••••••••••••• 61

15

16

COMPLETE FACTOR LOADINGS FOR AEA GROUP

SUMMARY FACTOR STRUCTURE FOR AEA GROUP

· . . . .· . . . .

62

63

17 CONGRUENCY COEFFICIENTS FOR AEA1 VERSUS AEA2 •• 66

COMMUNALITIES AND EIGENVALUES FOR THE AJA EQSTRUCTURE ••••••••••••••••

18

19 COMPLETE FACTOR LOADINGS FOR AJA GROUP

. . .· . . . .

67

68

vi

20

21

SUMMARY FACTOR STRUCTURE OF AJA GROUP • • •

CONGRUENCY COEFFICIENTS FOR AEA VERSUS AJA

· . .· . .

69

71

22 COMMUNALI TI ES AND EIGENVALUES FOR THE KOREAN EQSTRUCTURE ••••••••••••••••••• 72

· . .SUMMARY FACTOR STRUCTURE FOR KOREAN GROUP •

CONGRUENCY COEFFICIENTS FOR AEA VERSUS KOREAN

23

24

25

COMPLETE FACTOR LOADINGS FOR KOREAN GROUP . . • •

• •

73

74

76

26 CONGRUENCY COEFFI C I ENTS FOR AJA VERSUS KOREAN • • 77

27 ~OMMUNAL I TIES AND EIGENVALUES FOR AEA SECOND ORDERSTRUCTURE • • • • • • • • • • • • • • • • • 78

28 COMPLETE FACTOR LOADI NGS FOR AEA SECOND ORDERSTRUCTURE ••••••••••••••••••• 78

29 SUMMARY AEA SECOND ORDER FACTOR STRUCTURE • • 79

30 COMMUNALI TIES AND EIGENVALUES FOR AJA SECOND ORDERSTRUCTURE ••••••••••••••••• 80

31 COMPLETE FACTOR LOAD I NGS FOR AJA SECOND ORDERSTRUCTURE ••••••••••••••••• 80

32 SUMMARY AJA SECOND ORDER FACTOR STRUCTURE • • • • 81

33 COMMUNAL I TI ES AND EIGENVALUES FOR KOREAN SECONDORDER STRUCTURE •••••••••••••••• 82

34 COMPLETE FACTOR LOADINGS FOR KOREAN SECOND ORDERSTRUCTURE •••••••••••••• • • • 82

SMR WITH EQ VARIABLES PREDICTING AEA VERBALABILITY ••••••••••••••••••

35

36

SUMMARY KOREAN SECOND FACTOR STRUCTURE . . . . . 83

84

37 SMR WITH EQ VARIABLES PREDICTING AEA SPATIALABILITY •••••••••••••••••• . . 85

38 SMR WITH EQ VARIABLES PREDICTING AEA PERCEPTUALSPE ED ••••••••••••••••••••• 86

39 SMR WITH EQ VARIABLES PREDICTING AEA MEMORY. 87

40 SMR WITH EQ VARIABLES PREDICITNG AES SPEARMAN 'G' 96

41 SMR WITH EQ FACTOR SCORES PREDICTING AEA VERBALAB I LITY •••••••••••••••••••• 89

vi i

42 SMR WITH EQ FACTOR SCORES PREDICTING AEA SPATIALABILITY • · • · · · • • · • • · · • · · · · · • 89

43 SMR WITH EQ FACTOR SCORES PRED ICT ING PERCEPTUALSPEED · • • · · • · • • · • · · · • · • · · · · 90

44 SMR WITH EQ FACTOR SCORES PREDICTING MEMORY 90

45 SMR WITH EQ FACTOR SCORES PREDICTING AEASPEARMAN'S 'G' • • · • · · · · · · · • · · • 91

46 SUMMARY OF SMR TABLES FOR AEAs • · · · · 92

47 SMR WITH EQ VARIABLES PREDICTING AJA VERBALABILITY • · • · • • • • • • · · • • • · · • · • 94

48 SMR WITH EQ VARIABLES PREDICTING AJA SPATIALABILITY · · • · · • · • · · · • · • · · · · · • 95

49 SMR WITH EQ VARIABLES PREDICTING AJA PERCEPTUALSPEED · • • • · • • · · • · · · • · · · · • · • 96

50 SMR WITH EQ VARIABLES PRED ICTING AJA MEMORY · • 97

51 SMR WITH EQ VARIABLES PREDICTING AJA SPEARMAN 'G' 98

52 SMR WITH EQ FACTOR SCORES PREDICTING AJA VERBALABILITY. • · • • · · • • · · · · · · · · • · · • 99

53 SMR WITHEQ FACTOR SCORES PREDICTING AJA SPATIALABILITY. • · • · • • • · · • • · • · · • · • · • 99

54 SMR WITH EQ FACTOR SCORES PRED ICT ING AJAPERCEPTUAL SPEED · · · · · · • · • • · · · • · · 100

55 SMR WITH EQ FACTOR SCORES PRED rCT ING AJA MEMORY 100

56 SMR WITH EQ FACTOR SCORES PREDICTING AJA SPEARMAN'G' • • • • • • • · · · • • · • · • · • · 101

57 SUMMARY OF SMR TABLES FOR AJAs · • • • · · · · • ~ 02

58 SMR WITH EQ VARIABLES PREDICTING KOREAN SPATIALABILITY. • · • · • · · · · · · • · · · · · · · · 104

59 SMR WITH EQ VARIABLES PREDICTING KOREAN VERBALABILITY. · · • • • • • • · • · • • · · · · • · • 105

60 SMR WITH EQ VARIABLES PRED ICT ING KOREAN MEMORY · 106

61 SMR WITH EQ VARIABLES PRED ICTING KOREAN ROTAT IONALSPEED • · • • · · • · • · · • • · · · · · · · · 107

vi i i

62 SMR WITH EQ VARIABLES PREDICTING KOREAN SPEARMAN'G v •••••••••••••••••••••• 108

63

64

65

66

SMR WITH EQ FACTOR SCORES PREDICTING KOREANSPATIAL ABILITY. • • · · · · · • • · · • • • • • 100

SMR WITH EQ FACTOR SCORES PREDICTING KOREAN VERBALAB IL1TY • • . • . · • • • • · · · • · • · • · · · 109

SMR WITH EQ FACTOR SCORES PREDICTING KOREANMEMORY • . • . . · · • · • · • • · · · • · • • • 110

SMR WITH EQ FACTOR SCORES PREDICTING KOREANROTATIONAL SPEED · • • • • · • • · • · · • • · • 110

67 SMR WITH EQ FACTOR SCORES PREDICTING KOREANSPEARMAN'S 'G' ••• •••• • ••••• 111

· . • 11268

69

SUMMARY OF SMR TABLES FOR KOREANS • • • • •

SPEARMAN RHOs FOR EQ-ABILITY PATTERNS ACROSSABILITY AND ETHNIC GROUP •••••••••• · . 115

70 CONGRUENCY COEFFICIENTS OF FACTORS ACROSS GROUPS& SIMPLE CORRELATIONS OF EQ FACTORS WITH COGNITIVEABILITIES •••••••••••••••••••• 119

71 COEFF ICIENTS OF CONGRLC NCE FOR SES,NORC FS, .ANDACCULTRN •••••••••••••• • • • • • • 124

72 TOTAL COGNITIVE VARIANCES ACCOUNTED FOR BY THE 16FACTORS AND 45 ORI GINAL EQ VAR IABLES • • • • • • 135

ix

LIST OF ABBREVIATIONS

• • • • •

• American of Japanese Ancestry

• American of European Ancestry

• • Acculturation factor

• •

• •

. .· .AJA

ACCUL TRN

AEA •

BBL • • • • • • • Behavioral Biology Laboratory

• • •

CTYRURAL

DEVPPREG

• • City-rural factor

• Developmental and pregnancy problems factor

EQ · . . . . . • Environmental questionaire

• Expected NORC factorEXPNORC •

FAMLYAGE

FAMLYSIZ

FTLDNPRG

· . .· . . .• • • •

• • • •

Family age factor

Family size factor

Fetal deaths and number pregnancies factor

IQ • • • Q • • • Intelligence Quotient

• •· . .

MOBILITY

MAG BOOKR

MOOD

• •

• •

• • Mobility factor

• • Magazines and books read factor

• Mood factor

NORCFS

NORC · . .. .

• •

• •

• Nati onal Op l nion Research Counci 1 (usua l l y refersto socio-economic classification of occupation)

• NORC factor

· . . .

• • •NURSERY •

PARRATG ••

PRVATSCH

• •

• Nursery school factor

• Parental rating factor

Private school factor

• • School work factor

• • • •

· . . .READMATH

ROOMMATF

SCHOOlWK

SELFRATG

• •

· . .

Read versus Math factor

Roomate factor

• Self rating factor

SES • • • • • • • Socio-economic status factor

x

SMR ••••••• Stepwise multiple regression

SOCPARFS •••• Social participation factor

SPELLMTH •••• Spelling versus Math factor

WEALTH ••••• Wealth factor

YREDCATE • • • • Years of education and age factor

xi

PROBLEM

The nature-nurture controversy over intelligence has been

going on since Francis Galton published Hereditary Geniu$ in

1869. If the discussion is to proceed past a bi-polar view,

ways in which both nature and nurture affect intelligence

must be explored.

One prob l em in expl or i ng the nurture side has been

finding the key variables affecting cognition and

understanding how they interrelate to one another. Many

environmental variables relating to cognitive abilities have

been reported (Jencks, 1972; Johnson & Medinnus, 1974;

Loehlln, Lindzey, & Spuhler, 1975; and Vandenberg, 1975),

but how they interrelate to affect cognition Is unclear.

Also, little is known about whether dimensions derived from

similar environmental variables will be similar or different

across different ethnic groups. Will the EQ factors relate

in the same ways or different ways to the cognitive

ab l l l ties?

This paper will report how dimensions of environment

differ or are similar for three ethnic groups and how these

dimensions relate to cognitive abilities within each group.

BACKGROUND

Early measures of intelligence

Francis Galton started a controversy about the nature of

intellect in 1869 by publishing Hereditary Genius, where in

he claimed that genius defined as outstanding accomplishment

in various fields of endeavor was Inherited. Using a

criterion of eminence that included only one out of every

4,000 persons in Great Britain, he studied 977 men. On a

basis of pure chance only one of their number could be

expected to have an eminent relative; instead there were

332. From these results, he made a argument that inheritance

was the source of eminence in men.

In 1873, A. de Cando11e, a Swiss, wrote a reply to

Galton, claiming that environment was the chief factor in

producing scientific genius. He had studied over 500 eminent

European scientists and found wealth, leisure, scientific

traditions, good education, availability of libraries and

laboratories, freedom to express opinions, and geographical

location In a temperate zone were all positively related to

scientific creativeness. This was the start of the

nature-nurture debate which continues today.

R. L. Dugdale (1877) took a different approach,

publishing a book titled "The Jukes". The Jukes chronicled

over three genera t ions, the fami 1y tree of five sis ters

whose offspring were characterized by criminality,

immorality, pauperism, and feeblemindedness. Dugdale's work

opened the whole range of intelligence from genius to

retardation for examination.

Early attempts to create intelligence tests

At the end of the 1800's psychologists were beginning to

explore ways of quantitatively measuring intelligence. As

early as 1884 Galton opened a laboratory at the

International Health Exhibition in London measuring not only

anthropometric traits, but strength of grip, accuracy in

bisecting an angle, accuracy in bisecting a line, and many

other sensory abilities. In the United States, J. McKeen

Cattell (1890) coined the word 'mental tests' referring to

tests performed in his laboratory such as rate of movement,

reaction time for sound, judgment of a ten second interval,

etc. Cattell, like Galton, believed that the testing of

simple sensory faculties would lead to an understanding of

higher mental functioning.

In 1895 Alfred Binet and Victor Henri in France wrote a

paper saying the higher mental functions should be measured

directly. This paper and two subsequent papers from the

United States did much to undermine Cattell's approach.

Sharp (1899) working out of Titchener's laboratory at

Cornell, published a study supporting Binet's position and

in 1901 Wissler published a study from Cattell's own

laboratory showing that the psychophysical measures did not

correlate well with class standing or with each other.

Binet's 'test of intelligence'

In 1905 Binet and T. Simon developed the first successful

test of general intelligence. In 1904, Binet had been

appointed to a committee to identify retarded children in

the French school system, so that they might be sent to

special classes. Binet questioned teachers to find out what

kinds of tasks childern at different ages were able to

perform. He selected a number tasks which the normal child

was able to pass at each age. Since some children scored

better and some scored worse than the 'average child' -

taken as the norm for their age -- educators and clinicans

were now able to assign a 'mental age' to each child. In

1912 William Stern suggested that an intelligence quotient

(IQ) could be formed by dividing a child's mental age by his

chronological age and multiplying by 100. Thus the famous

'Intelligence Quotient' or 'IQ' came into being. Binet had

not based his test on theory or tied it to a strict

definition, but had used strictly empirical methods to

measure a child's ability level. Binet, replying to

criticism that his 'metrical scale of intelligence' had no

zero point, said:

I have not sought •• to out l ine a method ofmeasurement in the physical sense of the word, but only amethod of classification of individuals. The proceduresthat I have described will make it possible, when theyare perfected, to place a person before or after anotherperson or persons, but I do not think that we can measureone of their intellectual aptitudes in the sense that wemeasure a length or volume. (1898)

Binet had chosen an empirical approach based upon

consideration of the normal distribution underlying it. This

represented a brilliant and workablp. method for measuring

development, that has been adapted by almost all

intelligence testers since then.

Terman's work

Lewis Terman, working at Stanford University, adopted

Binet's approach and in 1916 published the Stanford-Binet

Intelligence Test. Terman's use of 2,300 subjects in

constructing the test, represented a strong improvement over

Binet's total sample of 50. Terman also adopted Binet's

theoretical view stating:

wi 11 unders tand, of course, that no s i ng l ealone will determine accurately the general

intelligence. A great many tests are required;two reasons: (1) because intelligence has manyand (2) in order to overcome the accidentalof training and environment. (1916)

The readertest used1evel ofand foraspects;influence

Due to Terman's careful standardization, the 1916

Stanford-Binet Intelligence Test was quickly adopted by

educators and clinicians and was widely used until Terman

published a revision in 1937.

The problem of a 'definition' of intelligence

Binet's test of intelligence was a practical tool to

identify retardates. Vandenberg (1966) points out that,

early In his studies Binet

••• relinquished the hope of basing his work on adefinition of intelligence, and instead used empiricalmethods to determine the average child's ability at agiven age.

Binet did not define his test as a measure of general

intelligence; however, the process of mental development

became linked in the public mind to a quantity of innate

intelligence. Boring's 1923 suggestion is well known: that

we should define intelligence as what the tests test. Terman

(1916) said that Intelligence was the Individual's capacity

to think abstractly and use abstract symbols (Johnson &

Medlnnus, 1974). Stanley Porteus (1941 ) emphasized

planfulness, and the capacity for long term perspective.

David Wechsler, developer of the Wechsler Adult Intelligence

Scale (WAfS), gave this definition in 1944:

Intelligence is the aggregate of global capacity of theindividual to act purposefully, to think rationally andto deal effectively with his environment.

"Quot capita tot sententlae"; seems to apply to the

concept of Intelligence Ci •e. as many meanings as

individuals). H. E. Garrett (1946) stated the problem of

defining intelligence.

Such "def in It ion", 1ike the t ime-worn sho t-iqunprescription can hardly fail to hit the troublesomewhere, but just where is not entirely clear. Omnibusdefinitions are In general too broad to be wrong and tovague to be useful.

So what is Intelligence? The definition Is particularly

elusive. It is like certain other key words in our culture

courage, honor, humor, love, nature for which we have

a certain intitutive feel, but whose definition is so

elusive. To define intelligence is to explain It and that is

something that can not presently be done.

To understand something more fully Is to quantify and

describe it more accurately. This is what has happened to

the definition of intelligence. I would like to present an

analogy from an essay by John Ruskin. Ruskin sets himself

the task of defining greatness in art and he does it in the

fo 11ow i ng way.

DEFINITION OF GREATNESS IN ART

Painting, or art generally, as such, with all itstechnicalities, difficulties, and particular ends, isnothing but a noble and expressive language, Invaluable asthe vehicle of thought, but by itself nothing. He wholearned what is commonly considered the whole art ofpainting, that is, the art of representing any naturalobject faithfully, has as yet only learned the language bywhich his thoughts are to be expressed. He has done just asmuch towards being that which we ought to respect as a greatpainter, as a man who has learnt how to express himselfgrammatically and melodiously has towards being a greatpoet. The language Is, Indeed, more difficult of acquirementin the one case than in the other, and possesses more powerof delighting the sense, while it speaks to intellect; butit is, nevertheless, nothing more than language, and allthose excellences which are peculiar to the painter as such,are merely what rhythm, melody, precision, and force are inthe words of the orator and the poet, necessary to theirgreatness, but not the tests of their greatness. It is notby the mode of representing and saying, but by what isrepresented and said, that the respective greatness eitherof the painter or the writer is to be finally determined .•••

If I say that the greatest picture is that which conveysto the mind of the spectator the greatest number of thegreatest ideas, I have a definition which will include assubjects of comparison every pleasure which art is capableof conveying. If I were to say, on the contrary, that thebest picture was that which most closely in1itated nature, Ishould assume that art could only please by imitatingnature; and I should cast out of the pale of criticism thoseparts of works of art which are not imitative, that is tosay, intrinsic beauties of colour and form, and those worksof art wholly, which, like the Arabesques of Raffaelle inthe Loggias, are not imitative at all. Now, I want adefinition of art wide enough to include all its varietiesof aim. I do not say, therefore, that the art is greatestwhich gives most pleasure, because perhaps there is some artwhose end is to teach. I do not say that the art Is greatestwhich Imitates best, because perhaps there is some art whoseend is to create and not to imitate. But I say that the artis greatest which conveys to the mind of the spectator, by

any means whatsoever, the greatest number of the greatestideas; an I call an idea great in proportion as it isreceived by a higher faculty of the mind, and as it morefUlly occupies, and in occupying, exercises and exalts, thefaculty by which it is received.

If this, then, be the definition of great art, that of agreat artist naturally follows. He is the greatest artistwho has embodied, in the sum of his works, the greatestnumber of the greatest ideas.

Ruskin opens by stating art is nothing more than an

expressive language, and learning to paint objects naturally

is simply learning the language of the medium. Just as

painting skills: sense of color, sense of proportion,

illusion of depth, etc. are important to an artist,

cognitive skills such as verbal, spatial, memory, reasoning,

perceptual speed, etc. are important tools for the

intellect. Ruskin goes on to say greatness in art is the

greatest number of the greatest Ideas. Intelligence could be

defined this way, but we could only measure it in a post-hoc

way such as through scientific awards and peer recognition.

This is the weakest part of Ruskin's argument. What is a

great idea? Ruskin alludes to appreciation by a higher

faculty of the mind (i.e. intelligence). This brings all of

Watson's arguments against faculty psychology to mind. At

present we are at the tools stage in Ruskin's argument with

regard to understanding intelligence.

As will describe, later, intelligence has come to be

regarded as being composed of overlapping, interacting

cognitive abilities. Psychological tests measuring memory,

verbal ability, spatial ability, perceptual speed, and

reasoning are viewed as components of intelligence. Boring

was right because he limited his definition. The tests do

define intelligence, but today they define different aspects

or processes/approaches that reflect the intellect. Testing

is at the stagp. of measuring the development of cognitive

'skills-tools-approaches-processes', but has not reached the

level of understanding how these tools are used to

synthesize new ideas. The definition of intelligence remains

a philosophical question although an operational definition

for this study will be given in the method section.

Intelligence testing arose from a practial need to

discriminate between individuals with regard to their

capacity for learning. The method came from empirical

findings and .not from a theoretical structure. Charles

Spearman was later to put a theoretical foundation under

intelligence testing, but many challenged his conclusions.

Quantitative advances and Spearman's 'g'

In 1875 Francis Galton, while walking, sought the

protection of a wall from a rainstorm. He describes in his

book Memories (1908) that while standing there the Idea came

to him of how the postlve or negative relationship between

two traits could be summarized in a mathematical statistic.

He relates:

As these lines are being written, the circumstances underwhich I first clearly grasped, the importantgeneralization that the laws of Heredity were solelyconcerned with deviations expressed in statistical units,are vividly recalled to my memory. It was in the groundsof Naworth Castle, where an invitation had been given toramble freely. A temporary shower drove me to seek refugeIn a reddish recess in the rock by the side of thepathway. There the idea flashed across me, and I forgoteverything else for a moment in my great delight.

Galton's great delight was to become the foundation for

multivariate research. His brilliant student, Karl Pearson,

developed the subject of his delight into the well known

Pearson product-moment correlation coefficient.

The field of probability and statistics has blossomed in

this century and psychology along with many other

disciplines

coefficient

has

and

drawn from it. Pearson's correlation

Ronald Fisher's analysis of variance

statistics are the underpinnings of most psychological

research today.

At the beginning of this century Charles Spearman was

using Pearson's new statistic to find relationships between

abilities measured in his research. Working with this data

he developed his famous 'two factor theory of intelligence'.

He showed that whenever a group of abilities are related, it

can be determined how much of the variance of each ability

is in common with a general functioning factor and how much

is specific to that ability. He presented a formula by which

the common and unique variance of an ability could be

separated. His theorem of general intelligence was stated

thus:

Whenever branchesdissimilar, thenappear wholly duewith some commonFunctions). (1904)

of intellectual activity are at alltheir correlations with one anotherto their being all variously saturatedfundamental Function ( a group of

Binet and Terman, although both impressed with Spearman's

logic, doubted his conclusions. Binet answered:

He (Spearman) regards his conclusion (that sensorydiscrimination and school achievement are expressions ofthe same unitary factor) as profoundly Important. It ispossible. We ourselves are profoundly astonished at it, •• • (1905)

Terman not faulting Spearman's logic, but his

conclusions, said:

• •• that there Is a correspondence between what mayprovisionally be called 'General Discrimination', and'General Intelligence' which works out with greatapproximation to one or absoluteness seemed to me asabsurd then as it does now. (1932)

Other theorists presented different interpretations of

the same basic type of data. E. L. Thorndike working with

animals presented a theory of connectionism:

• •• find connections of varying strength between (a)sltutations, elements of situations, and compounds ofsituations and (b) responses, readiness to respond,facilitations, inhibitions, and directions of responses.• • • Learning is connecting. The mind is man'sconnection-system. (1931)

A Scottish psychologist, G. H. Thomson, offered a

'sampling' theory by which

• .j. each test calls upon a sample of the bonds whichthe mind can form, and that some of these bonds arecommon to two tests and cause their correlation. (1951)

Neither theory made much headway against Spearman's 'g',

probably because neither refuted his theory, but were simply

alternate ways of explaining the facts. For those seeking

general causes and sinlple functioning, Spearman held sway.

Spearman had taken Binet's method which had a underlying

gaussian distribution and could be described by probability

theory, and by using Pearson's correlation coefficient

created a mathematical model for a theory of intelligence.

His explanation was not accepted by everyone, but was the

most parsimonious one at the time.

Thurstone's Primary Abilities

The replacement of Spearman's 'g' came when many began

modifying Spearman's approach. A problem with Spearman's

theory was that tetrads in the correlation matrix sometimes

failed to vanish leaving significant amounts of variance

unexplained by the single 'g' factor. Leon Thurstone dealt

with the problem by presenting a solution called multiple

factor theory. This theory abandons 'g' in favor of as many

factors as necessary. Thurstone states:

Beginning with Spearman's famous paper in 1904, there wasa quarter of century of debate about Spearman's singlefactor method and his postulated general intelligencefactor g. Throughout that debate over several decades,the orientation was to Spearman's general factor, andsecondary attention was given to the group factors andspecific factors, which were frankly called 'thedisturbers of g' • • •• The development of multiplefactor analysis consisted essentially in asking thefundamental question in a different way. Starting with anexperimentally given table of correlation coefficientsfor a set of variables, we did not ask whether itsupported anyone general factor. We asked instead howmany factors must be postulated in order to account forthe correlations. (1952)

After extensive analyses of many test batteries,

Thurstone regarded seven abilities as best established:

verbal comprehension, word fl uency, number ( i . e.

computational facility), space (i.e. spatial visualization),

associative memory, perceptual speed, and reasoning. These

comprise Thurstone's well-known Test of Primary Abilities

(PMA). Thurstone's approach has become the accepted way to

study intelligence

abilities.

by studying cognitive processes or

Advantages of separate abilities

Vandenberg (1966 ) 1 is ts the conceptual advantages

measurement of separate abilities has over a global approach

to intellect. Different abilities may have different rates

of development, be more or less suitable for prediction of

success at different tasks, more or less susceptible to

mental illness or brain damage, stable over different age

ranges, and vary between cultural groups. Cyril Burt (1919)

and Henry Garrett (1946) developed theories suggesting there

is greater differentiation of abilities as a person ages.

Lienert (1960, 1961) developed a divergence hypothesis which

suggested that children of greater abil ity would have a more

differentiated structure of abilities and resemble older

children. These studies have tried to integrate the

developmental process into the theory of intelligence and

show that abilities become more distinct as a person ages.

Multiple ability theory has allowed new concepts of mental

processes to be explored.

Criticism

theorists for

though

their

has been directed at the factor

very success at finding mental

'abilities'. R. Tuddenham stated:

Yet the very proliferation of factor theory has reducedthem from hypothetical constructs to mere interveningvariables, and robbed the factor theory of the claims toelegance and parsimony which had been Its basic

justification • • • the ironic possibility exists thatThurstonlans, like the Spearmanlans before them may yetfind themselves with a horde of factors almost asnumerous as the sampling theorists' bonds. (1962)

Tuddenham

Intelligence

presented six criteria that a theory of

must deal with: organization, maturation,

structural and functional pathology, heredity, and

environment. He writes,

First, let us consider the things which a satisfactorytheory of intelligence should do. It should provide arational basis for the construction of single-score andmulti-score tests of Intelligence and aptitude; it mustaccount for the empirically known relationships amongthem--and between them and the usual criteria ofeducational and vocational success. This is to say, itmust make provision both for the generality and for thespecificity of individual differences In cognitive areas.It must provide an explanation of the curve of change Inability throughout the entire life span from earliestinfancy to senescence, and allow for the fact thatperformances Involving different test content wax andwane at different rates and shift In theirdifferentiation from one another at different lifestages. It must take into account the Influences of braindamage and disease, sensory and motor impairment,Infection, and drugs of various kinds. It must comprehendthe facts on family resemblance in level and organizationof abilities, accumulated In fifty years of research onthe role of heredity in human differences. At the sametime It must account for the demonstrated Influence ofeducation and training in altering test performance,including data on differences associated with schooling,class level, ethnic group membership, language,generation, etc. And lastly, it should be at leastcongruent with psychological theories of learning andmotivation and theories on other levels of investigationand description, e.g., neurophysiology, biochemistry,genetics, etc.

Tuddenham also introduces the premise that In all

behavior involving the manipulation of symbols content and

process covary. Factors such as 'g', fluency, speed, and

reasoning may Involve more process than content, while

number, verbal, spatial, and memory are more content skills.

Certainly the conceot of intelligence will continue to

change. Just as Spearman was able to give his theory

substance by using a mathematical model, the theory of

intelligence will be strengthened by drawing on the

contributions from fields as anthropology, communication

theory, genetics, medicine, physiology, and many others. The

quest for understanding of intelligence is just beginning.

Envl ronmental Infl uences on Intell i gence

Co-variation between environment and heredity

The problem of separating environmental and hereditary

effects wi th ina measure shoul d be cons i dered before

reviewing the literature on how the environment relates to

cognitive abilities. That both genes and environment are

necessary Is a given fact. Without genes an organism cannot

exist and without environment an organism cannot develop.

The question this paper tries to answer is what are the

environment dimensions important to cognitive abilities and

how do they interrelate.

First, there is a 'minimum' environment needed for

homosapiens to develop into what would be considered a

normal human being. The evidence of feral childern,most

notab 1y the s to ry of ' the wi 1d boy of Aveyron' (I ta rd,

1932), indicates that attributes which have set humans apart

from the rest of the animal world -- reasoning, language,

and social conduct -- are not innate and must be developed

through socialization. Studies with lower animals by Har l ow

(961) and Scott & Fuller (1965) indicate that a certain

minimum amount of social interaction, most Importantly from

the mother, (or peers, i.e. monkeys) is needed for normal

development in higher mammals (e.g. monkeys and dogs).

Physiological differences In brain chemistry have been shown

to be related to differing degrees of environmental

stimulation (Bennett, Diamond, Krech, & Rosenweig, 1964>

That a minimum of environmental nurturing is required Is

evident.

Considering two well known variables, sex and

soclo-economic status (SES), will Illustrate the problems of

the nature-nurture discussion. The classification of sex, of

being either male or female, will be shown to be an

important variable in its influence on cognitive abilities.

It Is also a variable that shows the difficulty in

partitioning the effects of environment and gene action. The

X and V chromosomes produce the differences between the

sexes, but thousands of years of cultural heritage have

placed certain expectations on males and females. If

eminence was taken as the criterion for Intelligence

throughout history, sex would have been a key discriminator.

Vet to assert that males excelled because of their superior

intelligence would cloud rather than clarify the issue. The

variable of sex has two independent forces co-varying within

it: that of chromosomal differences and that of different

cultural expectations placed on the two sex roles.

Socio-economlc status Is another example of the problem

of disentangling hereditary and environmental effects. The

question is whether high SES parents supply an enriched

environment thus raising their offspring's intelligence or

whether high intelligence offspring rise to high SES levels

and subsequently have above average childern. Can

environment affect genetic expectation and is a 'minimum'

environment necessary for genetic influence to show itself?

Conversely, is there a 'minimum' genetic inheritance with

which a person exposed to his 'perfect' environment may

aspire to genius? Involved is not only the two independent

effects of heredity and environment, but the interaction of

these two forces. Interaction in this context means that

persons of different genotypes will be affected differently

by the same environment; that one person's intellectual

growth may be stimulated by certain conditions which would

not affect or may retard another's mental growth. These

interactional effects should be kept in mind. They cloud the

nature-nurture issue and the difficulty in partitioning

their effects has been at the center of the controversy from

the beginning.

Ways in which the environment may act

Vandenberg (1966) introduces the botanist's terms:

stunting, hothouse: and fertilizer, to conceptualize

environmental effects on behavior. Neglect <Skells,1966) is

known to be able to stunt normal intelligence. Whether

environmental enrichment also can act as a hot house forcing

an early bloom that is no different from a normal bloom or

can act like fertilizer producing better quality is a

question. The role of the environment as fertilizer is an

attractive concept; it would allow for the enrichment of

Individuals simply thro~gh the addition of the missing

environmental ingredients. Unfortunately, the evidence

presented will show that many important variables are such

that they can be neither added nor subtracted from the

environment.

Environmental Effects on Intelligence

Environmental categories*

R. A. LeVine (1970) in a review of cross-cultural

studies, contrasts industrial versus agarian cultures and

gives four lines of explanation for cognitive differences

besides gene pool differences existing between cultures:

malnutrition resulting from below minimum

protein-calorie requirements stunting brain and early

development processes in non-industrial cultures;

2) early cognitive enrichment and stimulation in

IndustrIal cultures providing children with toys,

puzzles, games, interactions, and situations for development

of symbolic as well as physical skills;

3) differences in social motives childern of

industrial societies being trained in self-reliance,

achievement, delayed gratification which promotes

intellectural development versus nonindustrial peoples

fosterl ng dependence and passive obedience in their

childern; and

4) broad differences in cultural milieu -- children's

early and pervasive exposure to values and beliefs in an

industrial culture which provide a different ideational

context for cognitive development than in folk and agrarian

cultures.

*1 would like to-thank Steven Vandenberg for access to anextensive monograph dealing with influences on cognitiveabilities. For an expanded treatment of many areas presentedherein, please see Vandenberg (1975).

Nutritional effects

Adequate nutrition has long been known to be Important to

good health and prevention of disease. It Is useful to

consider four periods of nutritional effect: prenatal, early

childhood, adolescence. and adult. Studies of starvation

among adults, usually during wartime (Keys, Brozek,

Henschel, Mickelsen, & Taylor, 1960), show that starvation

during this period does not permanently affect cognitive

ability. The studies do show a change in motivation and

interests, if not ability, for persons who experience

starvation during childhood and adolescence. After coping

with starvation, a youth's goals may change -- possibly with

loss of the ambition, curiosity, and drive needed for

intellectual accomplishments.

J. Cravioto (1968), summarizing work in this area,

suggests that severe malnutrition is most harmful if it

occurs within the first six months of life. Harrell,

Woodyard, & Gates (1955) support this conclusion. They

studied pregnant women in low-income groups who had

deficient diets. The experimental group received a dietary

supplement during pregnancy and lactation while the control

group received placebos. When tested at four years of age,

the offspring of the experimental group had a significantly

higher mean IQ. In a study over a longer period, Stein,

Susser, Saenger, & Marolla (1972) studied Dutch persons born

during famine years In World War II. Persons showed lower

birth weight, but at age 19 did not differ in intelligence

from normals. Animal studies (Altman, 1971), however, show

that nutritional deprivation during gestation and infancy

are harmful to brain development. Prolonged, rather than

temporary, starvation is indicated in permanent stunting of

development. Subjects regaining proper diet show a 'catch

up' phenomenon (Tanner, 1963) regaining normal stature and

seemingly normal intelligence when tested as adults. This

evidence shows the human organism to be especially adaptable

and tough within certain extreme limits. Low birth weight

does seem to be a factor, but within the limits of normal

variation, the relationship to intelligence is small, the

correlation being .06 (Vandenberg, 1975).

Socio-economic status

Since Galton's original work, much attention has centered

on the importance of socio-economic status (SES). Galton's

argument would be that superior people rise to eminence and

pass on their abilities to their offspring; while the

environmentalist would claim that the upper classes are able

to give their offspring advantages that promote their

intellectual growth not available to others less fortunate.

Much interest has centered on this area with many

investigators stressing different aspects of SESe Variables

that have been considered important are: prestige of

father's occupation, education of the parents, measures of

wealth, books in home, and many others. Factor analytic

studies of SES measures (Knupfer, 1946; Kahl & Davis, 1955;

and Atherton, 1962) have found two dimensions: 1)

occupation-education and 2) quality of home and furnishings.

Almost all studies have found a positive relationship

between the SES index used and scores on cognitive tests

Numerous studies emerging from many Western countries, some

dealing with thousands of subjects, have shown a relation

between SES and intelligence (Byrnes & Henmo~ :1936; Burt,

1943; and de Montmol1 in, 1958). Duncan and others (1972)

reanalyzing the Harrell and Harrell (1945) data found a

correlation of .42 between intelligence and SES; a similar

coefficient of .45 was found In the Stewart (1947) study.

Many studies have also related parental SES to specific

cognitive abilities of offspring. Havighurst and Breese

(1947) reported that abilities of 13 year olds had

correlation with SES of: .32, (Number); .42, (Verbal); .23,

(Spatial); .30 (Word Fluency); .23, (Reasoning); and .21

(Memory). Douglas (1961), Bacher (1966), and Meili & Steiner

(1965) all found a stronger relationship with verbal ability

than between SES and the other abilities tested. The

relationship of spatial ability to SES is comparatively low,

although it is known to have a high genetic component

(Vandenberg, 1971). Nuttin (1965) notes that there is wide

overlap and variability within the SES groups with many in

the lower SES groups scoring in the upper ten percent on

each test.

Studies are in conflict regarding whether SES is more

highly correlated with intelligence among males than

females. Kagan and Moss (1959) and Honzik (1963) reported a

significant relationship to appear for girls at an earlier

age than for boys. Schull and Neel (1965) found boys scores

more related to SES in 9 out of 11 cognitive tests, while

Werner, Bierman, and French (1971) found the opposite trend.

Buck, Gregg, Stravraky, and Subrahanian (1973) found

inconsistent results.

Wechsler (1949) reported studies on over 7,000 children

aged 6 to 11 showing that SES correlations generally

increased as age increased. Coleman (1966), reporting on a

federal study evaluating differences in educational

opportunity throughout the United States, concluded that

differences in ability were mainly associated with factors

in the students' background and not with differences between

schools. He found only 10 to 20 per cent of the variance in

ability could be attributed to differences between schools,

with the rest being within school variance. Jencks, Smith,

Acland, Bane, Chohen, Gintis, Heyns, and Michelson (1972),

summarizing others' research, estimated that if everyone's

public schooling could be equalized, cognitive inequality in

adults could be reduced from 5 to 15 per cent, although they

conclude that this estimate is very rough. Even 10 per cent

of the variance indicates a sizeable effect as a result the

type of school a student attends, even though this effect is

not as powerful as it sometimes is thought to be.

A similar conclusion was reached from testing 9,400

students from different types of school in Stockholm,

Sweden. No relationship was found between ability levels and

the different types of school attended (Svensson, 1962).

Dockrell (1966) testing middle and lower class chi ldren in

England found, while the type of school attended was

unimportant in middle class children, presumably as a result

of the enriched environment they were exposed to, the type

of school did make a difference for lower class children,

es pec l all yin verbal abi 1i ti es. Ranucci (1952) found that

high school geometry classes did not affect subject's score

on a spatial relations test; however, Blade and Watson

(1955) reported that subj ects who had taken a co 11 ege

engineering course had improved scores on spatial ability.

There is, however, a possibility of biased sampling in the

Blade and Watson study. Meyers (1958) found that United

States naval cadets with previous mechanical drawing courses

were no different from other cadets on spatial-relation

tests. In a 1mostall stud ies repor ted where SES was

measured, there was a strong positive relationship with

intelligence. Verbal ability ~hows the highest correlation

with SES, with other abilities being positively related in

varying degrees.

Birth order and family size

Effects of birth order and family size on intelligence

have generated much interest. These two measures are related

in that later borns must come from families of size two or

larger. Early studies found a negative correlation between

intelligence and family size (Scottish Council for Research

in Education, 1933; Cattell, 1936; and Nuttin, 1970). This

effect was confounded by SES because lower SES families had

more offspring than higher SES fami lies. In 1970, Kennett

and Cropley studied high SES children and found no relation

between family size and ability. Other studies (Higgins,

Reed and Reed, 1962; and Bajema, 1963) have found that high

SES parents may have as large or larger families than low

SES parents and that earlier studies had been flawed by not

takeing into account the fact that low IQ persons often had

no offspring.

Throughout history, first borns have held special favor

(Genesis 25.31,). Sampson (1964), reviewing the qualities of

first borns found them to be more likely to gain

intellectual eminence, to seek company when anxious, to be

less likely to express aggressive feelings, to be less

sociable, empathetic or sympathetic, and to have lower

self-esteem. Altus (1966), Breland (972), and Poole and

Kuhn (l 973) present evi dence that firstborns are

over-represented among National Merit finalists and college

graduates. Speculation about these effects have centered

around firstborns' increased contact with adults, more

attention received from parents, and lack of older sibs as

models. Zajonc (1976) has proposed a confluence model in

which the effects of birth order are mediated by age gaps

between childern.

Personality relations

Ferguson and Maccoby (1966) studied the relationship

between Thurstone's Primary Abilities and personality traits

in fifth graders. They found higher verba 1 ab i 1 i t v

correlated with dependency on adults, and less social

contact with peers; while numerical ability correlated with

assertiveness, interpersonal competence, and independence.

Jensen (1973) using the Junior Eysenek Personality Inventory

with children ages 9 to 13 found no correlations with the

verbal or non-verbal sections of the Lorge-Thorndi ke

intelligence tests or with the Raven Progressive Matrices

tests•. He did find moderate relationships between

personality scores and achievement. After the effects of SES

and IQ were removed, he found 9.1% of the variance explained

by personality score for Whites, 8.1% for Blacks, and 6.1%

for Chi cano s ,

Parental attitudes

Differences in,' parental attitudes, especially the

mother I s approach to ch i 1drear i ng, have rece i ved much

attention. Skeels (1966) gave dramatic evidence of the

importance of early stimulation. Thirty-nine years ago,

Skeels persuaded authorities to move 13 of 25 children from

an orphanage they were into an ins t i tut ion for retarded

adults. The children sent to the institution were assigned,

one or two to a ward where they received individual

attention from patients, attendants and nurses, whi 1e the

children left in the orphanage received little individual

attent ion. The ch i 1dren who were sent to the menta 1

institution showed improved IQ scores compared to a decrease

shown by those left in the orphanage. The very magnitude of

the differences reported by Skeels, recently has brought the

the study into guestion. It has been criticized for post hoc

controls and sampling problems (Longstreth, 1974).

Bayley and Schaefer (1964) found many relationships

between maternal behavior and intelligence in the Berkeley

Growth Study. In the first year of life, punitive maternal

behavior affected boys' IQs positively and girls' IQs

negatively. After the first year of life, the picture

reversed with boys' IQs being retarded by and girls' IQs

showing a positive relation to strictness of maternal

behavior in the 13 to 54 month interval. Girls' IQs do not

show any relationship to maternal behavior in the 5 - 18

year range, but the boys' correlation remains negative to

strict maternal behavior. Between 5 and 18 years of age,

boys' IQs showed a positive correlation with 'positive

evaluation' and 'equalitarianism' of the mother.

Bronfenbrenner (1958), Zigler and Child (1969), and Hess

(1970) have reviewed research on how different SES groups

view their children and their intellectual development. They

find that lower class families spend less time reading to

their children, spend less money on non-essential toys and

educational trips, and expect less of their children

educationally, though not in duties around the home. Lower

class families use corporal punishment while middle class

families 'lecture' and withhold love or special privileges.

Middle class mothers spend more time with their children

encouraging questions, and interacting in a more 'didactic'

way. This may be partly a function of middle class mothers

having more leisure time to interact with their children.

Lower class children are found to have less of an inner

'locus of control I -- the feeling they can control, at least

in part, their own life. Peer influences would reinforce

class effects, since most children associate with children

of the same SES group.

Schaefer (1958) developed the Parent Attitude Research

Instrument (PARI) which measures three parental attitude

dimensions concerning children: I} love vs. hostility, 2)

encouragement of autonomy vs. restrictive control, and 3}

consistent vs. lax or inconsistent control. Becher and Krug

(1964) caution that the PARI is only useful for upper-middle

class parents. Milner (1951) found that children whose

mothers were more concerned about their achievement did have

higher ability than those whose mothers showed less concern.

Moore (1968) studying eight year old children, removed SES

effects and found the following correlations: mother's

vocabulary score, .23; toys, books, and experiences, .45;

example and encouragement, .31; emotional atmosphere, .49;

and adjustment of the child, .42.

Wolf (1974) developed a scale of three factors that

favored intellectual development: press for achievement

motivation, press for language development, and provisions

for general learning. He found intelligence to be correlated

.69 with his total scale, while an index of social class was

unrelated to intelligence. Dave (1963) developed a similar

questionnaire aimed at educational achievement and found a

correlation of .80 between ability and total achievement. An

index of educational environment and various achievement

scores ranged from .55 to .77. Mosychuk (1969) related

family environmental data of 100 children to their WISC

scores. He obtained the following four factors obtained from

his environmental questionnaire: 1) aspiration - planfulness

harmony 2) authoritarian - overprotection 3) activity,

environmental interaction, and 4) female-language

stimulation, and related them to the children's WISC IQ to

obtain correlations of .42, -.18, .19, and .24 respectively.

Marjoribanks (1972) tested eleven year old boys from five

ethnic groups: Canadian-Indians, French-Canadians, Jews,

Italian-Canadians, and White Anglo-Saxon Protestants. He had

a middle and lower class breakdown within each ethnic group

and used results on four tests: verbal, numerical,

reasoning, and spatial. A home interview session obtained

information from the parents to yield eight environmental

factors. Estimated reliability coefficients for the

environmental scales ranged from a low of .66 for mother

dominance to a high of .94 for press for achievement. The

order of the ratings, whether the raters were the same, and

if the ratings were blind, is unfortunately not mentioned.

The correlations between these variables and the cognitive

abilities for the total group are shown below. Marjoribanks

does not show within ethnic group correlations.

TABLE 1

Correlations between Mental Abilities and EnvironmentalFactors (Marjoribanks, 1972)

Environmental Factors Ab i 1 i ty

Verbal Number Reasoning Spati al

1. Press for achievement · · .66** .66** .39** .22**2. Press for activeness. · • .52** .41** .26** .22**3. Press for intellectuality .61** .53** .31** .26**4. Press for independence. · .42** .34** .23** .105. Press for English • • • · .50** .27** .28** .18**6. Press for ethlanguage · • .35** .24** .19** .097. Father dominance. · • · · .16* .10 .11 .098. Mother dominance. · · · • .21** .16* .10 .04

Multiple correlation • 72*** .72*** .43*** .32**

*p<.05**p<.Ol

***p<' 001

The multiple correlations indicate that verbal and number

ab i 1 it i es are much better explained by Marjoribanks'

environment factors than reasoning and spatial. In verbal

and number abilities there is a large percentage of variance

accounted for. For verbal ability Marjoribanks attributed

16% of the variance to environment, 11% to ethnicity, and

34% to covariation of ethnicity and environment; for number

ability the respective percentages are: 19%, 3%, and 31%.

In another study (Broman, Nichols, and Kennedy, 1975)

prenatal, neonatal, and early childhood variables were

related to IQ at four years of age. Blacks (N=14,548) and

wh i tes (N=12,203) were the two ethnic groups studied. All

predictor variables accounted for 25% (white boys) to 28%

(whI te girls) of the variance for whites compared to 15%

(black boys) to 17% (black girls) for blacks. Some important

predictors were education of the mother, socio-economic

index, number of prenatal visits, number of pregnancies, and

maternal age.

A study by Hilton and Myers (1967) gives good visual

illustration of how various intelligence measures are

related differently to environmental measures. Their results

are shown below in table 2. It can be seen that for the

prediction of different abilities, different environmental

measures are important, and the range of variance accounted

for 1s between 30 and 40 percent.

TABLE 2

BACKGROUND and EXPERIENCE QUESTIONNAIRE

Predictors: SEQ Scores Dnl1'Sounpll\' All aeadomle bo7a iD 12th grada In Sprln,. lOB!

FIGURE 13 A stepwise multiple regression prediction of 12th·grade test scores and rank in class of 1,206 boys, showing the contribution of background variables to be different for differentcriteria. (Hilton and Myers, 1966)

WN

..ttl>~

Level 01oceupallOnDI plane

continued

AmounLor homework dono

Tim. epent In hlgh·eklllIICIl.III..

Inloreotl~ lan",ages

Tlmo spenl on ~;chanlcnl thing. (-)

Intereat In mnlhcmnllc8t

Amount 01 thought onvarloueteUbJects

Summary of nonaeadomlcIntoreols (-)

tTime opontln 10w·.kll1

Dell,'lII•• (-)

I

Rank-in-O...

Am""nt 01hfsh-Io"e1 readln,

FIGURE 13

CEEB Amerle... malo..,.

TIme .penl on,current .rr,ln

Time spont t.1kl"' to parenl. (.)

.Amountof mOd~um-I,v.I readln,

Lent 01 oco"pallonal plan,

TIme ,penf In Illw·eklllaollvlll .. (-)

. fAmount 01thought on,

various .ubJecta

tPar.nto' eduoallon

tTime .pont on mechanleatthin,. (-)

ISumma..,. or nonaeademlc

Inloroal. (-)

.j

Time epent on artwork .., home

Interealln lan",a,eat

Amount or thouChi onverloua fublecla

Porento' educallon

ILevol Ofoccur·,tional plana

tTime spont In low·aklll

aeUvmo, (-)

ISummary ot nonacademic

Inloro.I, (.)

CEEB EngllDh CompoalUon

Interest In mathematic,

Inlore.t in,EnsUsh (.)

Amount of hllholovol roadln,

Time npcnl tnlkIng to paronl' (-)•Amount 0' thought onvhrloUfi fl1bJacta

Parent" edu.allon

tTim. spcnlln 10w-,klU

aCllvlur (-)

,.", ..M1U_ ' '''''

Summary of nonacademicIntor ••t. (-)

SAT Math

Puent.' educallon

tAmount or thought on

VUloUl·ubJ.eta

~....=r-'_'.M

TIme ,pont in 10w·,klUacllvlUos (-)

ISumml.l7 of nOnAcademic

iDtoro.ta (-)

Amount of hlsh-level road1Dg

37

38

35

3t33

3231

30

29

28

27

28

25

2t23

22

Z1

20

1918

17

18

18

It

13

12

11

10

Crlter10lll SAT Vorbalf, of varl...ee

e"Plalned

::J;~

39

38

City environments

Little work has been done on how the general 'quality of

life' affects mental abilities; however, growing up in New

York City seems intuitively different from growing up in

Hawaii. How this difference affects mental growth, however,

is unknown. R. L. Thorndike (1939) did early work on factors

he judged to characterize 'the general goodness of life' In

cities. Using 297 variables from census data on 310 United

States cities, he developed a 'g' score. He described it as

follows,

A high g score means life for babies, education forchildren, parks and playgrounds, libraries and museums,the absence of slums and child labor, wide provision ofgas, electricity, telephones and radios, highwage-scales, and other aids to a good life.Thorndike believed that a certain level of wealth and the

personal qualities of the population were the important

aspects of the 'goodness of life' of cities. Moser and Scott

(1961) studying 60 variables on 157 towns in England and

Wales found the important dimensions to be socioeconomic

distribution, age of town (which is negatively related to

population growth), development after 1951, quality of

housing, and degree of over crowding. Hadden and Borgatta

(1965) performed eight analyses using 65 variables on 644

cities. Grouping the cities by size and type, they factor

analyzed the data and extracted very similar factors in all

analyses. These factors were: 1) socioeconomic status

distribution, 2) percent non-Whit~, 3) age composition, 4)

presence of educational center, 5) residential mobility, 6)

population size, n foreign born concentration, 8)

population size, 9) presence of wholesale center, 10)

presence of retail center, 11) presence of manufacturing

center, and 12) presence of heavy industry and communication

center. These studies show differences in city environments,

but if and how these aspects affect intelligence are

unknown.

National environments

Cattell (1950) analyzed correlations of demographic,

economic, and health statistics of many different countries

in order to study characteristics of nations. The general

dimensions he found were: size, area, population; wealth,

standard of living and average income. Rummel (1972) in the

Dimensionality of Nations project has studied 230 variables

for 82 nations. in summary, he reports these dimensions: 1)

economic development; 2) size; 3) political orientation

(totalitarian or not); 4) population density; 5) Catholic

culture; 6) foreign conflict behavior; and 7)domestic

conflict behavior.~

Sawyer and Le Vine (1966) used a similar approach to

ethnological variables. They scaled 210 cultural

characteristics of Murdock's (1957) 'World Ethnographic

Sample' into 30 variables which they factor analyzed for 565

societies. They found nine factors: 1) agriculture, social

stratification and political integration; 2) animal

husbandry, male involvement, domestication of animals; 3)

fishing and marine hunting; 4) hunting and gathering; 5)

nuclear family household, no extended family structure,

small household size; 6) patril ineality; 7)matrilineality;

8) cross-cousin marriage; and 9) socio-political

stratification.

At present, it is still unclear how much independent

contribution of intelligence each environmental factor makes

and how these dimensions combine to create a total effect.

Further work is needed and more eclectic approaches should

yield information regarding not only which factors are

important, but also how they combine to shape intelligence.

objective was to relate the environmental

each group to their cognitive factor scores.

PAGE 37

OBJECTIVES

As stated in the problem, one important question in the

discussion of environment is the identity of the key

variables and how they relate. Studies on the factor

structure of cognitive abilities (Michael, 1949; Flaugher &

Rock, 1972, Humphreys & Taber, 1973; and DeFries et al.

1974) all found very similar dimensions of intellect across

different ethnic groups. Similar approaches to the

environment seem to be lacking; although, as previously

noted, Majoribanks (1972) has rated different groups on

dimensions of home environment using a scale that he

devised. have (Wilson, 1975) reported environmental

dimensions for a group of offspring. In a factor analysis of

the EQ variables the first principal component was an

'ethnicity' dimension. After rotation of the factors the

ethnicity relationship was fragmented among many other

dimensions.

My first objective therefore was to perform factor

analyses of these environmental variables within ethnicity

using offspring from three ethnic groups (Americans of

European Ancestry-AEA's, Americans of Japanese

Ancestry-AJA's, and Native Koreans-NK's) to determine if and

how the environmental structure changed from one group to

another.

My second

structure of

Cognitive factor scores for the cognitive tests existed for

each ethnic group and were employed as prediction criteria

in a stepwise multiple regression analysis. The two

procedures taken together gave a picture of how

environmental variables are related across ethnic groups and

how these environmental structures relate to cognitive

abilities.

METHOD

Data Collection

The subjects are offspring of families particpating in

the grant "Geneti c and Env i ronmenta 1 Bases of Human

Cognition" (Grant HD-06669), which is administered by the

Behavioral Biology Laboratory (BBL). Blood and saliva

samples were obtained from each person tested In Hawaii and

then the subjects were tested on a battery of cognItive

tests. The tests were administered by the group method and

a tape recorder was used to standardize instructions and

time limits. At the end of the testing sessIon each person

filled out an environmental questionnaire. There was a

parental and an offsprIng environmental questionnaire with

specific questions for each group of persons.

Sample Population

There are 1,745 offspring from three ethnic backgrounds.

The first two ethnic groups are AmerIcans residing in

Honolulu, Hawaii. One consists of 1,122 Americans of

European Ancestry (AEA) and the second of 380 Americans of

Japanese Ancestry (AJA). The third group represents 243

Native Korean's (NK) from the city of Choon-Chun, Korea.

Both parents had to be from the same ethnic group in order

for the offspring to be classified In that ethnic group.

Honolulu. The data collection from Korea was supported by

BBL and collected under the supervIsIon of Dr. Jong-Young

Park. Park (1975) reports prelIminary conclusions

concerning sex effects, and of certain EQ relatIonships to

cogni t ion.

PAGE 40

All Families were paid to participate.

Table 3 below gives the mean age for each subject group

broken down by sex.

Table 3 -- Mean age for each subject group

AEAs AJAs KOREANS

15.7 2.215.9 2.1

MALEFEMALE

X

16.516.6

S.D.

2.83.0

N

549571

x16.717.3

S.D.

2.63.1

N

179200

x S.D.

Environmental Variables

In the fOllowing pages many abbreviations or acronyms are

introduced to more easily discuss the material. All of these

abbreviations are either defined in the Li st of

Abbreviations at the beginning of the paper of in Table 4

below.

EQ variables obtained for the AEA and AJA sample are the

same and have been taken from two different EQ's. One was

filled out by each offspring in the family, the other by

each parent, with some specific questions for the mother

(e.g. the mothers are asked about their pregnancies).

Though this study dealt with the environment of the

offspring, variables from the parent's EQ are included as a

result of their presumed effect on the offspring (e. g.

socio-economic effects, pregnancy problems, etc.).

Variables were chosen by the investigators because of their

reported influence on cognitive abilities. If the purpose

had been to study the effect of the environment on

personality, adjustment, health, or self-esteem the set of

variables chosen would have been much different. The

variables represent an diverse approach to environment. No

particular theoretical position was being tested, but rather

any environmental variable reported in the literature and

pratical to obtain was considered. Initially 103 variables

from the two questionnaires were considered; but through

discussions with my advisor and other investigators

condensed the variables to the 45 variables reported on

below. These variables are listed in Table 4.

Variable

AGEAMTTVANXIETY*BIRTHORDBOOKREADBOOKSOWNDEPRESS*DEVPPROB

ELEMINTRFAGEBIRFAMINCOMFATHAWAY*FATHNORC

FRDVISTSFJOBMOB

FRNDLANG*FYREDCGRADES

GRDVSFRDHANDWRITHOMEWORKHOSTILTY*HOUSEJOB*MAGEBIRMAGREAD*MATH

fv1YREDCNOFETALDNOPREGNURSERYPIDGIN*PREGPROBPSCHOLAR*

PTEMPERM*

READING

PAGE 42

TABLE 4.Explanation of EQ Variable Names

Expl anation

Age of subject at time of testing.Amount of television subject reports watching.Anxiety rating from Multiple Affect Check List.Birth order of subject.Amount of books read per month.Number of books in home.Depression rating from Multiple Affect Check List.Mother's report of whether she had developmentalproblems with offspring.Number of elementary and intermediate schools attended.Father's age at birth of offspring.Parent's estimates of family income.Was father absent for year or more?National Occupational Research Council's(NORC) rating of Father's occupation.Number of friends that visit the home per month.Father's NORC of first job subtracted from NORC ofpresent job.Amount of foreign language known.Father's years of education.A combination of elementary and intermediate schoolgrades.Grades of subject's versus grades of friends.With which hand does subject write?Average hours of homework done per week.Hostility rating from Multiple Affect Check List.Size of home.Does subject have job?Mother's age at birth of subject.Number of magazines read per month.A rank ordering of mathematical ability with threeother abilities.Mother's years of education.Number of fetal deaths.Number of pregnancies of mother.Whether subject attended nursery school.Amount of pidgin spoken in home and with friends.Mother's report of whether she had pregnancy problemsFactor score of scholar from parent's average rating ontwelve personal adjectives.Factor score of temperment from parent's rating ontwelve personal adjectives.with subject.A rank ordering of reading ability with three otherabilities.

* Variable not obtained from Korean subjects.

ROOMMATESCHOLAR*

SEXSIZECITYSIZESIBSOCIALPRSPELLI NG*

TEMPERMT*

YRSEDC

EXPNORCFJOBSATOWNHOMEPREPSCHTUTORDISCIPLN

SOCIABLE

HEALTHSPDISCIPN

PSOCABLE

PHEALTH

PAGE 43

Number of roommates the subject has.Factor score for "scholar" from the offspring's ratingsof themselves on the twelve personal adjectives.Sex of subject.Size of city in which the subject was born.Number of brothers and sisters.Chapin's (1942) index of social particpation.A rank ordering of spell ing ability with three otherab i 1 i ties.Factor score for temperament from the offspring'sratings of themselves on the twelve personal adjectivesYears of education subject has.

Variables unique to Korean subjects

NORC rating of offspring's expected job.An index of father's job satisfaction.Whether the parents owned home.Did subject attend prep school.Has the subject been tutored.The first factor score from the twelve adjectives,roughly corresponding to the AEAs and AJAs SCHOLAR.Factor score, roughly corresponding to AJAs' and AEAs'TEMPERMT.Factor score representing reported health.Parent's factor from the twelve adjectives. There issome resemblance to PSCHOLAR.Parent's second factor score corresponding somewhatto PTEMPERMT.Parent's report of health of offspring.

Computed variables

There are groups of questions within the EQ that deal

with particular areas in the environment. In many cases,

combinations of these variables represented a concept

better, allowed for clearer interpretation, and permitted a

condensation of information. These variables were of two

types. The first type emerged readily from factor analysis.

These are explored in detail subsequently in the paper. For

many questions, however, factor analysis was not suitable

and the variables were combined on logical bases. These

variables are presented with a short explanation.

The variable GRADES was a combination of elementary and

intermediate school grades. Because some subjects had not

yet reached high school this was used as an index of the

subject's school ability. For the same reason ELEMINTR was

a combination of the number of elementary and intermediate

schools the subject had attended. With regard to foreign

language ability each subject was asked how many languages

s/he knew and how well s/he could read, write, and speak

each language. A person could respond with a 'well' or a

'with difficulty' to each read, write, and speak question.

A subject was given two points for a 'well' response and

one point for a 'with difficulty' response. If a subject

knew no foreign languages and left the page blank, s/he

would receive a score of zero; if s/he knew three languages,

well in every category, s/he would receive a score of 18.

The range then was 0 - 18 for the new computed variable

lANGSKIL.

The variable PIDGIN was the sum of how much the person

spoke pidgin with friends and how much s/he spoke at home.

SOCIALPAR, standing for social participation, was computed

by a formula developed by Chapin (1942). It respresents

the sum of one times the number of civic clubs a person has

been in, twice the number of clubs the person still is in,

and three times the number s/he was or is an officer.

FJOBMOB represents the father's realized job mobility and

is the NORC rating of the father's first reported job

substracted from the NORC rating of his present occupation.

FAMINCOM is the sum of the father's and mother's estimates

of their income. PREGPROB and DEVPPROB represent whether

the mother reported any pregnancy or developmental problems

for the subject. FAGEBIR and MAGEBIR are the age of the

father and mother at the chi ld's birth and BIRTHORD is the

birth order of the offspring.

Korean EQ variables

The Korean environmental variables did not exactly match

those collected for the AEAs and AJAs. Some of the EQ

variables collected for AEAs and AJAs were not obtained for

the Korean sample (e.g. ANXIETY, HOSTILTY, DEPRESS,

FATHAWAY, FRNDLANG, JOB, MAGREAD, PIDGIN and SPELLING).

Some extra variables that possibly were important in the

Korean culture were obtained (e.g. FJOBSAT -- Father's job

satisfaction, TUTOR -- Whether offspring had private tutor,

PREPSCHL -- Whether offspring attended prep school, EDUCEXP

- Educational expectations, NORCJOB -- NORC of expected job

and OWNHOME -- whether parents own their home). Though there

are some differences between the Korean data set and the

American data set, approximately 80% of the variables are in

common to the two groups.

Factor analytic procedures

Factor analysis was the method used to reduce groups of

variables related to one other. The common factor analysis

model was used in every analysis unless otherwise noted. In

the common factor model the variance of each variable may be

divided as follows:

Xv = Xc + Xu , where

Xv = total variance of a variable,

Xc = variance common to the other variables in the

sampling universe. (i.e. the environmental universe)

Xu = variance unique to itself plus the error variance

(Xu = Xui + Xe)

In the common factor model an estimate of a variable's

communality (typically~ it is the squared multiple

correlation of all the other variables in the data set

predicting the variable) is placed on the principal diagonal

and an iterative procedure performed until the communalities

stablize. The Statistical Package for the Social Sciences

(SPSS) programs were used for the analyses. Common factor

analysis (or PA2 inSPSS) was used with an oblique rotation

using a delta of zero. An indirect obllmin rotation

procedure is used by SPSS.

In subsequent factor analyses, plus and minus signs for

the loadings of each factor, have not been changed. I

thought it best not to alter the results and report the

results exactly as they appeared in the computer printouts.

All of the original variables are oriented intitutively with

females and left handers given scores higher than males and

right handers.

Coefficent of congruence

The coefficient of congruence is used to compare the

factor structures from different ethnic groups. Gorsuch

(1974) gives Tucker's definitional formula:

LP pVI V2

C = ------------12 rLP .2 2:.P ~

i VI V2

C 12 is the co-efficient of congruence between factor 1

and factor 2

p VI are factor loadings for the first factor and p V2

are the factor loadings for the second factor. This method

has the capability of comparing structures where identical!

groups of variables are not used. In comparing the Korean

versus the American ethnic groups the coefficient is

computed for those variables which are in common to both

structures. As a result of the reflected signs of the factor

loadings from the different structures, some of the

coefficients appear with negative signs. What is of concern

here is the magnitude of the coefficient and not its sign.

Cognitive Measures

The cognitive measures are 15 tests that have been factor

analyzed into four abilities: verbal, spatial visualization,

perceptual speed and figure memory (DeFries et al., 1974).**

These fifteen test were given communalities of 1.0 and a

varimax rotation was used on the principle axis solution.

For the total population these four factors extracted 61.8%

of the variance and their factor loadings are shown on the

next page in Table 5. Also included is Spearman's 'g' which

is the first unrotated principal axis factor.

*Copies of the cognitive tests are on file at BBL forexami nat ion.

**The fifteen cognitive variables are given in order ofadministration, along with test times allowed and estimatedreliablities. The reliablities are test-retest reliablitieson over 300 subjects. The tests are: (i) Primary MentalAbilities (PMA) vocabulary, 3 minutes, .92; (ii) visualmemory, (VMI), 1 minute of exposure and 1 minute of recall,.37; (iii) things, (TH), (a fluency test), two parts, 3minutes each, .78; (Lv ) mental rotations, (MR), 10 minutes,.83; (v) subtraction and mUltiplication, (SAM), two parts, 2minutes, .94; (vi) Eli thorn mazes, (LAD), ("lines anddots"), shortened form, 5 minutes, .48; (vi l ) EducationalTesting Service (ETS) word beginnings and endings, (WBE),two parts, 3 minutes each, .80; (viii) ETS card rotations,(CR)" two parts, 3 minutes each, .85; (ix) visual memory(delayed recall), (VMD), 1 minute, .49; (x) PMA pedigrees,(PED), (a reasoning test), 4 minutes, .85; (xi) ETS hiddenpatterns, (HP), two parts, 2 minutes each, .76; (xi l ) paperform board, (PFB), 3 minutes, .76; (xiii) ETS numbercomparisons, (NC), two parts, 1.5 minutes each, .82; (x l v )Whiteman test of social perception, (SPV), (verbal), 10minutes, .62; and (xv) Raven's Progressive Matrices. (PMS),modified form, 20 minutes, .82.

TABLE 5.

Factor Loadings of Cognitive Abilities (AEA & AJA sample)

Verbal Spatial Perc. Spd. Memory Spear.------ ------- ---------- ------ ------

vac .80 .10 .25 .09 .71VMI .13 .08 .06 .85 .34Things .68 .22 -.09 .01 .55MR .16 .80 -.09 .05 .56SAM .20 .15 .81 -.02 .53LAD .04 .62 .13 -.01 .45WBE .67 .11 .27 .04 .62CR .13 .76 .18 .05 .63VMI .08 .05 .06 .85 .29PED .58 .28 .41 .17 • 75HP .32 .58 .26 .11 .69PFB .36 .64 .09 .07 .67NC .14 .13 .84 .14 .52SPV .71 .21 .08 .13 .66PMS .51 .54 .15 .10 .74

These four cognitive factors and the first principle

component are the criterion variables predicted in objective

two of this paper -- to determine how and in what way the EQ

variables relate to cognitive abilities within each ethnic

group. These factor loadings provide a feel for the factors

as defined by the different tests. Age has been shown to

be an important variable for these cognitive skills (Wilson,

DeFries, McClearn, Vandenberg, & Johnson, 1975), but the

factor scores referred to will not reflect age effects

because age-corrected scores have been used for all

analyzes. The factor scores also have been computed within

sex and ethnic group.

Korean Cognitive variables

As mentioned earlier the Korean data were collected under

the supervision of Dr. Park*.

PAGE 50

Every effort was made to

duplicate the tests, questions, and procedures used at BBL.

However, due to cultural restrictions, certain changes were

necessary.

Whiteman's test of social perception had to be eliminated

from analysis, because it was found that the social

situations depicted were too specific to the American

culture and were not meaningful to the Korean sample. The

word beginning and endings test had to be modified as a

consequence the ideographic and alphabetic nature of the

Korean language. The modified test asked the subjects to

generate words beginning with a specific symbol. (This

would be similar to asking for words which begin with a

certain letter.)

*Reliability estimates for the Korean sample are reportedby Dr. Park (975)' and were computed by means of theSpearman-Brown formula, the composite reliabilitycoefficient (CR), or the Kuder-Richardson formula (KR) fortests with a single score (Lord and Novick, 1968).

The test reliabilities are: (i) Korean vocabulary test(Voc), (KR) 0.87; (ii) visual memory, immediate recall(VMI), (KR)-O.75; (iii) things (TH), (CR)-O.71; (iv) mentalrotations, (MR), (KR)-O.92; (v) subtraction andmultiplication (SAM), (CR)-O.95; (vi) Elithorn mazes (LAD),not obtained; (vii) word beginnings and endings (WBE),(CR)-O.79; (viii) card rotations (CRT), (CR)-O.87; (J x )visual memory-delayed (VMD), (KR)-O.76; (x) pedigrees (PED),not obtained; (xi) hidden patterns (HP), (CR)-O.91; (xi l )paper form board (FPB), (KR)-O.85; (xiii) number comparisons(NC), (CR)-O.88; and (x l v) Raven's progressive matrices(PMS), (KR)-O.85.

The tests were factor analyzed and again a clear four

factor so 1ut ion was obta i ned. I t was however different

enough from that obtained from the Hawaii sample to require

intrepretation •• Males and females were combined to provide

adequate sample size. Table 6 below shows the four cognitive

factors plus Spearman's i g ' from a separate analysis.

TABLE 6 KOREAN COGNITIVE FACTOR LOADINGS

SPATIAL VERBAL MEMORY ROTATSPD SPEARVOC .14 .61 .05 -.03 .41VMI -.06 .26 .69 -.06 .36THINGS -.08 .71 .14 -.01 .37MR .21 -.02 .07 .58 .35SAMT -.07 .31 -.01 • 76 .35LAD .26 .47 -.15 .06 .38~~BET -.07 .64 .24 .13 .42CRT .13 -.09 -.08 .74 .24VMD .13 -.05 .83 -.03 .40PED .31 .50 -.03 .02 .46HPT .74 .10 -.25 .11 .49PFB .81 .11 .23 .14 • 75NCT .74 .12 .30 .09 • 72PMS .48 .07 .57 .14 .64

have changed only the name of the fourth factor, ROTATSP,

meaning rotational speed. They differ somewhat as shown by

the congruency table below.

TABLE 7 COEFFICIENTS OF CONGRUENCE FOR COGNITIVE FACTORSAEA & AJA VERSUS KOREAN

(AJA and AEA)VERBAL SPATIAL PERCPSPD MEMORY SPEAR'G

(KOREAN)SPATIAL 47 86 46 29 79VERBAL 71 37 18 68 77MEMORY 54 49 25 52 69ROTATSP 23 22 82 02 49SPEAR'G' 83 72 46 57 95

Factor analysis of attitude questions

Factor analysis was used to condense two sets of

questions, one filled out by the offspring and the other by

the parents. The questions were set up in a Likert format

from one to seven and are shown below. The subjects were

asked to rate themselves on the adjectives and the parents

were asked to rate their sons and daughters.

Easy to get along wi th • • • Hard to get along wi thDependable • • • • · UndependableStudious • · Uninterested in

studyingHardworking. • · LazyHappy • • • • • • · Sad or unhappyWell organi zed • • • • • • • DisorganizedPopu1ar • • • • • · UnpopularBright • • · DullBetter at math · • • Better at Englishthan at english than at mathEven tempered • • · Easily upset

or angeredRelaxed • • • • • Nervous and tenseHealthy • • • • • Sickly

Ratings by the parents were averaged to obta I n a parental

rating for each measure. The offspring's answers and

parental ratings were then factor analyzed separately. A

forced two factor solution gave the most interpretable

result. A three factor solution looked best for the Korean

group. Factor loadings and communalities for each variable

and the eigenvalues for the structures of the three ethnic

groups are shown in table 8.

Table 8Factor structure of offspring's attitude scores -- AEAs

FACTOR 2(SCHOLAR)STUD IOUSHARD\~ORK

DEPENDWELLORGBRIGHT

VARIABLEEASYDEPENDSTUDIOUSHARDWORKHAPPY\'JE LLORGPOPULARBRIGHTMATHENGEVENTEMPRELAXEDGHEALTH

COMMUNA LI TY0.340.410.530.520.420.380.320.360.040.310.470.24

FACTOR 1(TEMPERAMENT)RELAXED .73HAPPY .61EASY .58EVENTEMP .54POPULAR .50GHEALTH .50

FACTOR123456789

101112

EIGENVALUE3.881. 631.020.860.820.670.630.590.520.470.460.41

-.80*-.75-.57-.53-.46

PCT OF VAR32.413.68.67.26.95.65.34.94.33.93.93.4

Table 9Factor structure of parent's attitude scores -- AEAs

FACTOR 2(PSC HOLAR)

PSTUDYPDEPENDPHARDvJKPWELLORGPBRIGHTPEASY

VARIABLEPEASYPDEPENDPSTUDYPHARDWKPHAPPYPWELLORGPPOPULARPBRIGHTBMATHENGPEVENTEMPRE LAXPHEALTH

COMfvlUNA LI TY0.650.670.680.650.690.610.290.290.050.660.710.16

FACTOR 1(PTEt4PE RAf';1ENT)PHAPPY .83PRELAX .82PEVENTEM .81PEASY .80PDEPEND .53PPOPULAR .52

FACTOR123456789

101112

EIGENVALUE5.231.701. 070.930.720.590.410.320.300.280.270.18

-.85-.81-.81-.78-.53-.52

PCT OF VAR43.614.19.07.76.04.93.42.72.52.32.21.5

*Minus signs as appeared in analysis results

Table 10Factor structure of offspring's attitude scores -- AJAs

FACTOR 2(SCHOLAR)

HARDWORK .73STUD I OUS .70DEPEND .70WELLORG .66BRIGHT .62

VAR IABLEEASYDEPENDSTUDIOUSHARDWORKHAPPYWELLORGPOPULARBRIGHTMATHENGEVENTEMPRELAXEDGHEALTH

COMMUNALI TY0.500.530.520.530.530.460.380.400.090.320.460.30

FACTOR 1(TEMPERAMENT)

HAPPY .73EASY .70RELAXED .67POPULAR .59EVENTEMP .56GHEALTH .54DEPEND .50

FACTOR123456789

101112

EIGENVALUE4.381. 730.990.840.760.680.570.470.440.430.370.34

PCT OF VAR36.514.4

8.37.06.35.74.84.03.63.53.12.8

Table 11Factor structure of parent's attitude scores -- AJAs

FACTOR 2(PSCHOLAR)

PSTUDY .83PDEPEND .81PHARDWK .81PWELLORG .80PBRIGHT .68

VAR IABLEPEASYPDEPENDPSTUDYPHA RmoJKPHAPPYPWELLORGPPOPULARPBRIGHTPMATHENGPEVENTEMPRELAXPHEALTH

COMt·1UNA LIT Y0.580.670.700.660.740.640.490.480.190.660.750.26

FACTOR 1(PTEMPERAMENT)

PRE LAX .85PHAPPY .85PEVENTEM .81PEASY .76PPOPULAR .70

FACTOR123456789

101112

EIGENVALUE6.081.470.940.770.620.500.420.340.290.210.200.16

PCT OF VAR50.712.3

7.86.45.24.23.52.82.41.81.71.3

Table 12Factor structure of offspring's attitude scores -- Koreans

VARIABLE COMMUNALI TY FACTOR EIGENVALUE PCT OF VAREASY 0.44 1 3.97 33.1DEPEND 0.31 2 1.58 13.2STUDY 0.37 3 1.21 10.1HARmvK 0.30 4 0.87 7.3HAPPY 0.31 5 0.78 6.5WE LLORG 0.56 6 0.67 5.6POPULAR 0.57 7 0.65 5.4BRIGHT 0.54 8 0.63 5.3MATHENG 0.43 9 0.49 4.1EVENTEMP 0.24 10 0.41 3.4RELAX 0.48 11 0.40 3.3HEALTH 0.62 12 0.34 2.8

FACTOR 1 FACTOR 2 FACTOR 3(D ISC IPLI N) (SOC IA BLE) (HEALTH)

WELLORG .73 BRIGHT -.73 HEALTH .76RELAX .58 POPULAR -.72 RELAX .47STUDY .57 EASY -.66 EVENTEMP .47MATHENG .57 MATHENG -.47DEPEND .55HARDWK .54

Table 13Factor structure of parent's attitude scores -- Koreans

VARIABLE COMMUNALITY FACTOR EIGENVALUE PCT OF VARPEASY 0.33 1 4.18 34.8POE PEND 0.43 2 1.53 12.8PSTUDY 0.49 3 1.24 10.4PHARDWK 0.12 4 1.10 9.1PHAPPY 0.39 5 0.79 6.6PWELLORG 0.53 6 0.73 6.1PPOPULAR 0.62 7 0.53 4.4PBRIGHT 0.61 8 0.51 4.2PtllA THENG 0.16 9 0.41 3.4PEVENTEM 0.76 10 0.35 2.9PRELAX 0.33 11 0.33 2.8PHEALTH 0.86 12 0.29 2.4

FACTOR 1 FACTOR 2 FACTOR 3(OBEDIENCE) (PSOCABLE) (PHEALTH)

PEVENTEM .84 PPOPULAR .78 PHEAL TH .92PWELLORG .71 PBRIGHT .74 PRE LAX .45PDEPEND .63 PSTUDY .60 PHAPPY .44PSTUDY .56 PEASY .56PBRIGHT .51

All the variables listed In Table 4 have been described

and they represent the present measure of the environment.

The tables representing the factor analyses of the EQ

variables for each ethnic group. Also shown are congruency

coefficient tables giving an index of similarity between the

corrspondlng factor structures. The second part of the

results section will show how the environmental variables

and factors relate as a group to cognitive abilities through

stepwise multiple regression.

Stepwise multiple regression

Stepwise multiple regression is used to give a picture of

how the environmental measures, acting together, relate to

cognition. This technique gives a multiple correlation

coefficient that is a combined relationship of EQ variables

with a criterion score and which may be squared to give the

amount of variance accounted for by the variables considered

as a group. The strength of stepwise multiple regression Is

that it generates a picture of the variables important to

the prediction of the criterion by adding variables to the

equation In their sequence of Importance. Each new variable

added is an independent contribution to prediction of

criterion. The first variable inserted in the regression

equation Is always the one with the largest relationship to

criterion, then interrelationships of this variable with the

remaining variables are controlled for by partial

correlation. This process eliminates the Influence of the

first predictor variable, giving each of the remaining

predictor variables a new relationship with criterion. The

predictor variable with the highest new correlation is then

added to the regression equation and the process repeated.

Thus, each variable is added in the sequence of importance

and represents an independent contribution to the prediction

of the criterion. To give a comparison between the amount

of variance the 45 orginial EQ variables could explain as

compared to how much variance the EQ factor scores can

explain, two stepwise multiple regression analyses will be

presented for each ethnic group. In each case the original

EQ variables will be presented first to show how much

cognitive variance can be squeezed out of all the EQ

variables. The second analysis, involving the factor scores

will always account for less variance, but has the advantage

of showing how and to what extent areas within the

environment relate to criteria. Also included in each table

are the simple correlations of the EQ variables or factors

to each cognitive ability.

Spearman's rank correlations (rho)

A set of Spearman rank correlations (rho) are the last

results presented. Rho (Siegel, 1956) is a correlation

statistic which compares two rank orderings of attributes

and requires only ordinal data. In this case, the simple

correlations of the original environmental variables with

the cognitive abilities are used as data points. An example

will make this clear. There exist a set of environmental

correlations with verbal ability for each ethnic group. Rank

ordering the environment-ability correlations provides the

"6rder of the magnitude of the relations of the environmental

variables to verbal ability across ethnic groups. Thus it is

possible to determine the degree of similarity between

ethnic groups in the the relative influences of these

environmental variables on verbal ability. Performing this

procedure for each ability within each ethnic group gives 15

patterns of influence, and comparisons made within ethnic

groups across abilities, and within abilities across ethnic

groups. These two sets of comparisons are shown in the

results.

Operational definitions

Stevens (1935), presenting the concept of operational

definitions, said:

Only thosepublic andscience.

constructsrepeatable

based upon operations which areare admitted to the body of

To make the constructs used in this paper both clear and

·public, the following operations are defined. A cognitive

ability for a subject is operationally defined as the factor

structure loading of each test times the subject's z score

on that test summed over all tests. Therefore to say a

subject has a high verbal ability is to say s/he is more

likely to excel at qualities such as having a large

vocabulary, being proficient at naming the social situations

pictured in Whiteman's test, able to name items from a

general category (e.g. round, metal, etc.), naming words

which begin and end with specified letters, etc.

The degree of similarity between two factors from

different structures is operationally defined as their

coefficient of congruence. As the coefficient approaches

one they have a high similarity, as it approaches zero they

have no similarity.

RESULTS

EQ factor structure for the three ethnic groups

The factors are named and described but again the names

are only a conceptual handle and close examination of the

factor loadings is important. As a rule of consistency and

for easier presentation of such a large amount of data, the

factors that are similar across ethnic groups will be given

the same names. However, their actual similarities will be

shown in the congruency tables.

The factor structure for the AEAs is presented first,

with the eigenvalues and communalities in table 14 and the

factor loadings in table 15. Tables 16 and 17 provide

summary and congruency indices. Correspomding results for

AJAs and Koreans follow in tables 18 21, 22 - 25,

respectively.

TABLE 14 COMMUNALITIES AND EIGENVALUES FOR THE AEA EQ STRUCTURE

VARIABLE COMMUNALITY FACTOR EIGENVALUE PCT VAR SUM VAR

FYREDC 0.55 1 4.10800 9.1 9.1FNORC 0.93 2 3.30842 7.4 16.5MYREDC 0.50 3 2.69271 6.0 22.5NOFETALD 0.75 4 2.37201 5.3 27.7PREGPROB 0.19 5 2.14738 4.8 32.5DEVPPROB 0.41 6 1.98804 4.4 36.9AGE 0.77 7 1. 75520 3.9 40.8SEX 0.31 8 1.35541 3.0 43.8YRSEDC 0.97 9 1.27265 2.8 l~6 • 7SIZESIB 0.99 10 1.22745 2.7 49.4BIRTHORD 0.54 11 1.19614 2.7 52.1JOB 0.22 12 1.17102 2.6 54.7GRVSFRD 0.12 13 1.11087 2.5 57.1READING 0.67 14 1.03822 2.4 59.5SPELL ING 0.51 15 1. 06600 2.4 61.9MATH 0.99 16 1.02333 2.3 64.2HOMEWORK 0.20 17 0.99175 2.2 66.4NURSERY 0.08 18 0.96025 2.1 68.5BOOKSRD 0.44 19 0.93553 2.1 70.6MAGREAD 0.31 20 0.91488 2.0 72.6AMTTV 0.18 21 0.87816 2.0 74.6SIZEC ITY 0.11 22 0.80513 1.8 76.4HANDWRIT 0.01 23 0.79419 1.8 78.1ANXIETY 0.78 24 0.75924 1.7 79.8DEPRESS 0.77 25 0.73607 1.6 81.5HOSTI LTY 0.66 26 0.72660 1.6 83.1FATHAWAY 0.36 27 0.69369 1.5 84.6GRADES 0.39 28 0.66695 1.5 86.1MAGEBIR 0.88 29 0.64899 1.4 87.5FAMINCOM 0.43 30 0.62086 1.4 88.9BOOKSHM 0.38 31 0.58091 1.3 90.2FRDVISTS 0.07 32 0.54999 1.2 91.4SIZEHOME 0.43 33 0.52916 1.2 92.6ELEMINTR 0.30 34 0.48963 1.1 93.7FRNDLANG 0.21 35 0.46443 1.0 94.7SOCPAR 0.18 36 0.38176 0.8 95.6PIDGIN 0.09 37 0.34268 0.8 96.3PTEMPERM 0.77 38 0.29945 0.7 97.0PSCHOLAR 0.72 39 0.28921 0.6 97.7TEMPERMT 0.49 40 0.25388 0.6 98.2SCHOLAR 0.97 41 0.22474 0.5 98.7ROOMMATE 0.42 42 0.21054 0.5 99.2FJOBMOB 0.18 43 0.17517 0.4 99.6FAGEBIR 0.76 44 0.12133 0.3 99.8NOPREG 0.98 45 0.07121 0.2 100.0

TABLE 15 COMPLETE FACTOR LOADINGS FOR AEA GROUP

1 2 3 4 5 . 6 7 8 9 10 11 12 13 14 15 16

FYREDC 70 -10 05 04 01 06 -11 -11 31 -09 10 07 -15 -08 33 11FNORC 54 -04 01 12 05 02 -21 -08 -03 -08 03 10 -22 -08 88 01MYREDC 69 -15 -04 04 -01 01 -23 -09 02 -13 09 . 10 -14 01 11 15NOFETALD 06 03 06 05 03 -02 -02 01 85 -04 01 00 02 13 -03 07PREGPROB -01 03 13 01 -04 -01 03 04 14 -02 00 01 -01 43 01 06DEVPPROB -07 09 09 -03 04 -01 03 -06 05 05 -06 -01 03 61 03 -05AGE 00 -08 -09 . 86 10 -01 -04 -03 05 -06 06 -08 -15 -08 -05 01SEX 03 -02 04 02 19 -10 -07 18 03 -08 49 04 00 -07 -01 -06YRSEDC 07 -12 -07 98 10 -03 -04 -00 07 -08 11 06 -12 -05 -06 06SIZESIB. 03 06 99 -04 -08 02 -06 06 20 -05 01 05 04 26 03 -01BIRTHORD 02 08 49 -10 -05 02 -55 05 10 -10 -02 04 -15 03 15 -09JOB 03 -10 01 41 01 05 02 -03 03 -06 -06 -07 -15 10 00 11GRDVSFRD 13 -24 01 05 -10 -05 -03 01 -01 -16 25 07 05 03 -03 07READING 07 11 -07 07 73 -03 03 -08 06 10 09 -02 -04 02 -05 26SPELLING -13 00 03 -06 -13 01 -00 68 -02 08 06 -04 09 -04 00 01MATH 01 -12 04 -11 -68 02 03 -74 -07 -12 -13 06 -00 -01 Q5 -07HOMEWORK 14 -31 -07 24 -03 -03 -02 -04 -02 -22 29 10 -06 -00 -04 -08NURSERY 24 -11 -09 01 -01 03 -09 -04 -03 -04 01 05 -10 -05 -10 09BOOKSRD 15 -05 -03 02 32 01 09 -01 07 -01 37 -00 10 -00 -05 49MAG READ 12 -06 -02 11 11 02 00 04 04 -01 -05 04 06 -02 07 53AMTTV -27 08 01 -27 -13 06 12 01 -05 12 -14 -02 21 01 -05 02SIZECITY 03 -00 -05 10 08 01 -06 -05 02 05 -01 01 -30 -03 -06 -07HANDWRIT 03 01 -00 01 -04 08 05 -04 01 01 00 01 -01 02 -00 04ANXIETY -04 19 02 -02 -08 87 03 -00 -01 19 -04 -04 -01 -01 03 03DEPRESS 02 23 01 02 02 87 -03 -03 -01 21 00 01 -01 -02 -00 05HOSTILTY -00 21 01 -05 -06 80 00 -03 00 23 -07 -05 -05 -02 -00 -01FATHAWAY -23 -04 -00 -06 01 -04 17 00 -01 03 -01 -02 58 01 -12 -01GRADES 25 -35 -06 08 -08 -06 -06 -05 -00 -34 50 15 05 -07 05 17MAGEBIR 26 -02 03 07 02 02 -93 01 04 -08 04 00 -24 -01 11 -04FAMINCOM 56 -09 -07 14 02 00 -27 -09 -00 -12 01 28 -20 -06 32 09BOOKSHM 57 -08 09 06 -01 -00 -07 -04 10 -11 15 20 -14 04 17 29FRDVISTS 10 -03 12 04 -05 -00 -02 05 01 -11 -01 17 -01 07 10 10SIZEHOME 14 -03 28 -13 -08 -01 08 -03 05 01 05 56 05 12 07 06ELEMINTR -11 02 -04 -15 -01 01 29 05 01 08 04 07 49 -00 -10 09FRNDLANG 19 -14 -07 32 -02 -01 -02 -00 04 -10 25 16 -00 06 -02 21SOCPAR 14 -25 01 14 -01 -05 06 -00 00 -18 25 11 16 09 -02 22PIDGIN -02 08 03 -12 -07 -02 -01 01 -03 07 -19 -04 -13 14 04 -04PTEMPERM 07 -25 02 03 07 -25 -09 -07 02 -85 00 05 01 -01 -03 -01PSCHOLAR -08 42 01 -15 07 13 02 12 -03 75 -48 -04 -09 05 05 -00TEMPERMT 10 -58 -02 03 -09 -37 -04 07 06 -31 -14 07 04 -06 00 07SCHOLAR -11 98 07 -14 11 19 -01 06 05 33 -23 -10 -06 09 06 -07ROOMMATE -01 11 35 -05 -03 02 09 07 08 07 -06 -50 02 16 -03 03FJOBMOB 04 04 02 -05 -04 00 -00 03 -03 02 -02 05 02 06 41 05FAGEBIR 30 -OS 01 07 01 -01 -84 02 02 -12 04 06 -34 -08 12 01

i NOPREG 01 07 75 01 -04 -00 -05 02 77 -04 01 03 -02 28 -02 01

rr

TABLE 16SUMMARY FACTOR STRUCTURE FOR AEA GROUP

PAGE 63

1 2 3 4(SES) (SELFRATG) (FAMLYSIZ) (YREDCAGE)

FYREDC .71 SCHOLAR .98 SIZESIB .99 YRSEDC .98MYREDC .69 TE~~PERMT -.58 NOPREG .75 AGE .86BOOKSHM .57 HOME~I/ORK -.31 BIRTHORD .49 JOB .41FAMINCOM .56 ROOMMATE .35 FRNDLANG .32FNORC .54FAGEBIR .30

5 6 7 8(READMATH) (MOOD) (FAMLYAGE) (MATHSPEL)

READING .78 ANXIETY .87 MAGEBIR -.93 MATH -.74MATH -.68 DEPRESS .87 FAGEBIR -.84 SPELLING .68BOOKSRD .32 HOSTILTY .80 BIRTHORD -.55

TEMPERMT -.37

9 10 11 12(FTLDNPRG) (PARRATG) (SCHOOU~K) (ROOMMATF)

NOFETALD .85 PTEMPERM -.?5 GRADES .50 SIZEHOME .56NOPREG .77 PSCHOLAR .75 SEX .49 ROOMMATE -.50

GRADES -.34 PSCHOLAR .48SCHOLAR .33 BOOKSRD .37TH1PER~4T -.31

13 14 15 16(MOBILITY) (DEVPPREG) (NORCFS) (MAGBOOKR)

FATHAWAY .58 DEVPPROB .61 FNORC .88 MAGREAD .53ELEMINTR .49 PREGPROB .43 FJOBMOB .41 BOOKSRD .49FAGEBIR -. 3l~ FYREDC .33

FAMINCOM .32

* Only loadings above .3 are shown.

AEA Factors

The first factor could be described by social economic

status (SES) or parental education aqua l l y well. The

education of the two parents are the highest loadings, but

it is obvious that all the loadings fall under the larger

concept of SESe The scholar rating (SELFRATG), slbshlpsize

(FAMLYSIZ), and years of education (YREDCAGE) form the major

loadings for the next three factors with respective loadings

of .98, .99, and .98. Factor three was named SELFRATG rather

than SCHOLARF for consistency across groups. Factor five

(READMATH) is the rating of reading ability as superior to

math ability. All of the personality variables fall together

in factor six to form a MOOD scale. Age of the family

(FAMLYAGE) is factor seven and a r a t i ng of math over

spelling ability, factor eight (MATHSPEL). Number of fetal

deaths and number of pregnancies correlate to form factor

nine (FTLDNPRG). Factor ten (PARRATG) is the ratings of the

offspring by their parents. Factor eleven is a school work

(SCHOOLWK) dimension. Number 12 (ROOMMATF) shows that

sharing a room relates to the size of the house the family

lives in. Factor 13 (MOBILITY) seems to describe a range of

physical mobility in American families. Developmental and

pregnancy problems load together to form factor 14

(OEVPPREG). The NORC rating of the father is basically the

next factor (FNORCFS), with the amount of magazines and

books read (MAGBOOKR) the last factor.

The above factor structure represents the total AEA

....

sample (N=1122). Since a key part of this study is to

compare factor structures across ethnic groups and the AEA

sample was by far the largest group; it seemed proper to

divide the AEA sample in half to obtain a baseline

comparison of two EQ factor structures containing different

subjects, but drawn from the same ethnic group. The families

had been given consecutive family numbers as they registered

for the study so I divided the AEA sample into even and odd

family numbers with AEAl having a total of 580 offspring and

AEA2 a total of 543. The two structures were basically the

same, but for the change in sequence in which the factors

appeared. Only one factor was such that it might be renamed.

This was factor number ten, from the AEAl sample, SEXDIFF

(sex differences) which replaced MAGBOOKR of the AEA2 group

and the total sample. SEXDIFF is related moderately to

SCHOOLWK and READMATH from AEA2.

A congruency table showing all the interrelationships is

presented below with a table listing the factor names in the

their order of appearance. The numbers in parenthesis

represent the sequence number of the factor in each

analysis.

TABLE 17 CONGRUENCY COEFFICIENTS FOR AEA1 VERSUS AEA2

AEA1 SEQUENCE

SELFRATGFAMLYAGEFAMLYS IZYREDCAGEMOODSESREADMATHFTLDNPRGMATHSPELSEXDIFFPARRATGROOMMATFDEVPPREGFNORCFSMOB ILITYSCHOOLWK

123456789

10111213141516

AEA2

SESMOODFAMLYSIZYREDCAGEREADMATHFAMLYAGEMATHSPELPARRATGFTLDN PRGSELFRATGSCHOOUJKROOMMATFMOBILITYFNORCFSDEVPPREGMAGBOOKR

FACTOR

SESSELFRATGFAMLYSIZYREDCAGEREADMATHMOODFAMLYAGEMATHSPELFTLDNPRGPARRATGSCHOOUIJKROOMMATFMOBI LI TYDEVPPROBFNORCFSMAGBOOKR*READMATH

COEFFICIENT

(5,1)** 95(1,10) 94(3,3) 87(4,4) 97(7,5) 82(5,2) 96(2,6) -95(9,7) 87(8,9) -92(11,8) 94(16,11) -86(12,12) -51(15,13) 82(13,15) 80(14,14) 86(*,16) -77

** Numbers in parenthesis represent sequence number of thefactor in each analysis

AEA1 VS AEA2

CONGRUENCE COEFFICIENTS (ROWS BY COLUMNS):(AEA1 BY AEA2 )

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 29 -41 -20 27 -02 -01 08 -70 -09 94 -72 14 -09 -13 -35 222 53 02 04 18 -07 -95 09 -19 07 14 -13 09 -64 -38 -11 073 -09 -00 87 -19 06 -32 07 03 59 -19 05 67 07 -16 40 -214 22 -03 -13 97 -25 -08 10 -26 04 29 -28 -07 -42 -13 -17 315 -01 96 09 -08 09 02 01 43 -05 -53 24 -05 04 04 04 -046 95 02 -09 27 -17 -40 29 -32 09 33 -43 36 -50 -56 -16 517 -19 02 09 -22 82 -05 -01 -03 -Ol~ 08 -05 06 06 -02 09 -778 -12 05 -45 -16 19 19 -06 15 -92 04 12 -39 06 07 -29 -199 18 01 -11 -01 43 04 87 -23 -01 13 -15 04 -08 02 03 -07

10 -15 08 14 -31 55 -06 02 43 04 -22 69 -09 04 -05 41 -3511 -23 46 04 -24 08 19 -16 94 -05 -54 64 -19 16 16 23 -0412 -47 16 41 -18 11 18 -21 37 07 -42 50 -51 17 32 28 -2013 -26 -02 41 -05 00 10 -03 11 36 -17 08 29 17 11 80 -0114 -67 02 03 -05 03 42 -22 11 -02 -09 13 -22 39 86 03 -1315 -44 -11 04 -19 -00 57 -23 -02 -02 03 -13 09 82 32 -02 1716 41 -13 -04 28 -25 -05 12 -64 04 49 -86 34 -06 -19 -24 29

The next factor analysis of is the AJAs (N=380). Again

the eigenvalues, communalities, and factor loadings are

presented first, followed by a descriPtion.

COMMUNALITIES AND EIGENVALUES FOR THE AJA EQ STRUCTURETABLE 18VARIABLE

FYREDCFNORCMYREDCNOFETALDPREGPROBDEVPPROBAGESEXYRSEDCSIZESIBBIRTHORDJOBGRVSFRDREADINGSPELLINGMATHHOMEWORKNURSERYBOOKSRDMAGREADAMTTVSIZECITYHANDWRITANXIETYDEPRESSHOSTILTYFATHAWAYGRADESMAGEBIRFAMINCOMBOOKSHMFRDVISTSSIZEHOMEELEMINTRFRNDLANGSOCPARPIDGINPTEMPERMPSCHOLARTEMPERMTSCHOLARROOMMATEFJOBMOBFAGEBIRNOPREG

COMMUNALITY0.530.720.370.610.410.330.910.290.910.900.610.430.270.720.680.670.310.140.450.590.220.140.060.720.830.660.320.410.920.440.430.240.440.360.230.240.330.720.830.620.760.390.210.750.99

FACTOR123456789

101112131415161718192021222324252627282930313233343536373839404142434445

EIGENVALUE3.903453.411773.123822.620722.244192.082511. 789071.596621.437001. 328991.229611.208381.182861.143131. 115661. 060630.993060.919650.896900.843040.833400.807610.738100.683510.662190.624400.600620.568220.546210.525220.510020.486770.449190.436050.386460.354100.308330.275640.268850.229070.178870.163100.124170.065980.04196

PCT VAR8.77.66.95.85.04.64.03.53.23.02.72.72.62.52.52.42.22.02.01.91.91.81.61.51.51.41.31.31.21.21.11.11.01.00.90.80.70.60.60.50.40.40.30.10.1

SUM VAR8.7

16.323.229.034.038.642.646.249.452.355.057.760.462.965.467.769.972.074.075.877.779.581.182.784.185.586.888.189.390.591.692.793.794.795.596.397.097.698.298.799.199.599.899.9

100.0

TABLE 19 COMPLETE FACTOR LOADINGS FOR AJA GROUP

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

FYREDC 18 -12 59 06 -07 -03 -11 06 14 -03 13.-42 -05 -01 03 20FNORC 15 -09 82 -01 -03 -03 -13 05 12 00 07 -23 -01 09 11 18MYREDC 22 -14 36 -08 -12 03 -15 14 20 07 15 -38 03 15 04 09NOFETALD 10 -06 05 13 01 -00 08 -03 75 03 06 02 -06 -00 -07 -03PREGPROB -00 01 08 -08 03 03 08 -05 27 06 56 10 05 -01 01 06DEVPPROB 04 03 -03 10 -02 06 08 05 -04 -09 53 -04 -05 04 -11 -03AGE -94 02 -09 -07 -18 -09 -06 -10 -10 -01 -00 -03 16 -11 -17 04SEX -13 -03 -09 -12 07 -37 03 -19 -01 19 07 -08 07 -10 14 26YRSEDC -95 04 -11 -12 -19 -10 -07 -07 -10 -01 -01 00 15 -11 -14 08SIZESIB -01 -10 10 88 16 07 05 -04 20 -02 07 -08 09 -17 16 -05BIRTHORD 11 -02 -03 47 63 09 03 -03 03 04 06 -01 06 01 17 -05JOB -64 -04 -07 -04 -16 -05 01 -06 -02 -04 -03 11 10 -05 -09 09GRDVSFRD 07 -05 03 -01 15 -05 -13 04 02 36 -15 20 14 04 21 25READING -05 02 13 -06 -01 -78 -24 16 02 -04 -03 -08 -01 -02 -_03 025 pe 11 i ng - 01 -02 -00 11 07 -03 08 -80 05 -09 01 01 02 -05 04 -12MATH 11 -08 -08 07 01 72 11 46 -01 14 02 02 09 12 01 -05HOMEWORK -19 10 -07 -29 -07 03 -10 -02 -04 32 21 -28 25 02 01 15NURSERY 10 04 05 -09 -04 08 03 11 09 26 11 -08 05 -02 13 14BOOKSRD 03 02 -02 -05 06 -32 -59 -01 04 15 -12 -16 11 -04 12 13MAGREAD -02 -01 14 01 -03 -08 -75 09 06 07 -07 -07 -00 -04 06 04AMTTV 26 03 -09 07 06 04 -04 07 -12 -03 05 09 -11 16 10 -32SIZECITY 05 06 05 -01 -01 01 -04 02 -14 01 -04 -02 -02 11 31 -04HANDWRIT -01 -09 -01 03 -08 06 -03 03 01 -04 -16 07 -02 06 -00 -08ANXIETY -01 -84 -01 05 -00 06 -01 -07 05 -07 -08 -08 -14 -06 -07 01DEPRESS -04 -90 05 -01 04 01 01 -06 07 -18 -07 -07 -17 -00 00 -04HOSTILTY 07 -77 07. 09 -04 05 01 07 13 -22 -02 -09 -17 -11 -07 -06FATHAWAY -11 -05 -11 05 -10 -03 05 -04 -04 -01 02 00 04 -54 -02 05GRADES 01 -07 03 01 12 -11 -16 02 16 46 -06 -20 39 02 14 33MAGEBIR 26 01 -00 -01 93 -05 02 -04 -01 -01 00 -01 01 20 -06 -04FAMINCOM 05 -10 57 -12 -04 04 -09 12 06 24 10 -25 09 07 15 02BOOKSHM 10 -05 34 06 04 -15 -15 . 06 -03 10 -09 -55 11 07 07 14FRDVISTS 14 05 05 18 -03 -08 -08 -10 11 -07 -12 14 -02 -10 36 01SIZEHOME 13 -00 23 02 08 -02 -04 11 40 08 03 -06 23 -18 37 -17ELEMINT -03 -08 -02 -03 -19 -05 -14 -06 10 02 -04 -00 -10 -54 -05 07FRNDLANG -27 -11 -00 -18 -13 03 -21 -03 01 17 17 02 17 04 01 14SOCPAR -03 09 04 -03 -01 -06 -12 14 -05 14 09 -04 15 -04 02 43PIDGIN 11 07 -13 06 02 13 31 08 -10 -08 -04 41 -12 23 08 00PTEMPERM -16 20 01 02 04 06 -02 -01 -05 17 06 06 81 -00 -07 04PS CHO LAR -16 10 -09 -10 09 -02 -02 04 01 40 -04 -23 86 02 13 25TEMPERMT 07 43 07 08 03 -03 -09 09 -09 53 04 30 29 -04 06 -01SCHOLAR -07 22 -08 -04 -03 06 -19 10 -02 82 -04 -07 39 -02 -as 10ROOMMATE 16 04 -05 57 -04 06 01 -07 -08 -08 -10 15 -09 05 -05 -04FJOBMOB -01 05 37 08 03 -13 -02 -03 02 -12 -13 10 -02 03 04 -09FAGEBIR 20 00 -07 01 83 -08 05 -02 02 -00 -05 -00 06 25 -01 -02NOPREG 02 -11 10 81 15 05 05 -04 61 -03 07 -05 02 -15 04 -07

TABLE 20 SUMMARY FACTOR STRUCTURE OF AJA GROUP

1 2 3 4(YRECAGE) (MOOD) (SES) (FAMLYSIZ)

YREDC -.95 DEPRESS -.90 FNORC .82 SIZESIB .88AGE -.94 ANXIETY -.84 FYREDC .59 NOPREG .81JOB -.64 HOSTILTY -.77 FAMINCOM .57 BIRTHORD .47

TEMPERMT .43 FJOBMOB .37MYREDC .36BOOKSHM .34

5 6 7 8(FAMLYAGE) (READMATH) (MAGBOOKR) (SPELLMTH)

MAGEBIR .93 READING -.78 MAGREAD -.75 SPELLI NG -.80FAGEBIR .83 MATH .72 BOOKSRD -.59 MATH .46BIRTHORD .63 SEX -.37 PIDGIN .31

BOOKSRD -.32

9 10 11 12(FTLDNPRG) (SELFRATG) (DEVPPREG) (ACCULTRTN)

NOFETALD • 75 SCHOLAR .82 PRE.GPROB .56 BOOKSHM -.55NOPREG .61 TH~PERMT .40 DEVPPROB .53 FYREDC -.42SIZEHOME .40 GRVSFRD .36 PIDGIN .41

HOMHJORK .32 MYREDC -.38TEMPERMT .30

PSCHOLAR .85 ELEMINTR -.54PTEMPERM .81 FATHAWAY -.54SCHOLAR .39

16(SOCPARFS)

13(PARRATG)

14(MOBILITY)

15( CTYRURAL)

SIZEHOME .37FRDVISTS .36SiZECITY -.31

SOCPRGRADESAMTTV

.43

.33-.32


AJA Factors

Factors one and two closely resemble YREDCAGE and MOOD

from the AEA structure. Factor three seems to be a

combination of SES and FNORCFS from the AEA structure which

forms a more global SES factor. The next eight factors

mi rror factors shown in the AEA structure. They are

respectively: FAMLYSIZ, FAMLYAGE, READMATH, MAGBOOKR,

SPELLMTH, PTLDNPRG, SELFRATG, and DEVPPREG. However the next

factor, ACCULTRTN, requires interpretation. The number of

books in the home, and the mother's and father's education

load opposite from the amount of pidgin the offspring uses.

As the second order structure shows, acculturation is also

related to the SES dimension. Factors 13 and 14 resemble

PARRATG and MOBILITY of the AEA structure. Factors 15 and 16

are new and seem to be a city-rural dimension (CTYRURAL) and

a social participation factor (SOCPARFS).

TABLE 21 CONGRUENCY COEFFICIENTS FOR AEA VERSUS AJA

AEA SEQUENCE AJA FACTOR COEFFICIENT

SEX 1 YREDCAGE FAMLYSIZ <3,4) 92SELFHATG 2 MOOD MOOD (6,2) -92FAMLYSIZ 3 SES READMATH (5,6) -89YREDCAGE 4 FAMLYSIZ SPELLMTH (8,8) -87READMATH 5 FAMLYAGE MAGBOOKR (16,7) -87MOOD 6 READMATH FAfvlLYAGE (7,5) -85FAMLYAGE 7 MAGBOOKR FTLDNPRG (9,9) 83SPELLMTH 8 SPELLMTH YREDCAGE (4,1) -83FTLDNPRG 9 FTLDNPRG SES (1,3) 78PARRATG 10 SELFRATG MOBILITY (13,14 ) -71SCHOOLWK 11 DEVPPREG ACCULTRN (*,12) -67SIZHOMEF 12 ACULTRTN DEVPPREG (14,11) 62MOBI L1TY 13 PARRATG *SESDEVPPREG 14 MOB III TYNORCFS 15 CTYRURALMAGBOOKR 16 SOCPARFS

AEA VS AJA

CONGRUENCE COEFFICIENTS (ROWS BY COLUMNS)(AEAs BY AJAs )

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 17 -11 78 -08 16 -14 -37 25 26 23 14 -67 16 28 29 462 07 -21 -15 13 02 03 11 -06 04 -01 -11 02 -07 -02 -07 -223 14 -09 13 92 31 14 10 -08 47 -04 14 -03 06 -19 31 -164 -83 01 03 -21 -18 -22 -23 -10 -08 oL~ 06 -13 17 -06 -23 315 -19 08 07 -19 -05 -89 -40 -11 -04 -02 -07 -16 -01 -11 -07 196 02 -92 05 05 -01 10 00 -03 13 -22 -14 -20 -25 -06 -06 -087 -19 02 -23 -10 -85 02 -02 01 -08 -09 -07 18 -12 -46 -10 -058 -05 09 -13 10 10 -42 01 -87 02 -05 -07 13 01 -18 05 -049 -00 -08 11 53 13 -06 -10 -08 83 -02 17 -09 02 -15 02 -03

10 04 -26 -18 -03 -10 -03 10 -10 -03 -13 -16 00 -23 -07 -01 -1811 -10 -08 14 -14 04 -42 -35 -14 12 14 06 -38 01 -10 19 5012 08 -02 46 -17 09 -06 -22 21 34 25 16 '-37 26 -10 56 1713 03 02 -30 05 -36 -01 -07 -11 -01 -05 -04 21 -09 -71 -11 -0614 05 02 -02 44 02 10 12 03 36 -03 62 11 04 -08 06 -0615 23 -08 85 06 17 00 -14 13 18 08 09 -38 05 26 29 2016 -07 -07 32 -07 -10 -44 -87 12 21 22 -06 -39 17 -10 21 40

Here follows the Korean data (N=248).

PAGE 72

TABLE 22COMMUNALITIES AND EIGENVALUES FOR THE KOREAN EQ STRUCTURE


FATHNORC 0.87 1 4.12868 9.6 9.6FJOBSAT 0.22 2 2.90183 6.7 16.4NOPREG 0.71 3 2.62935 6.1 22.5EXPNORC 0.94 4 2.24873 5.2 27.7GRDVSFRD 0.39 5 2.07674 4.8 32.5READING 0.63 6 1. 84259 4.3 36.8MATH 0.58 7 1. 77169 4.1 40.9HOME~~ORK 0.22 3 1.60255 3.7 44.7NURSERY 0.41 9 1.51625 3.5 48.2TUTOR 0.46 10 1.40525 3.3 51. 5PREPSCH 0.33 11 1.33004 3.1 54.5BOOKSRD 0.23 12 1.23969 2.9 57.4AMTTV 0.15 13 1.12875 2.6 60.1SIZECITY 0.21 14 1. 12273 2.6 62.7OWN HOME 0.71 15 1.07614 2.5 65.2ROOMMATE 0.80 16 1. 01146 2.4 67.5HANDUSE 0.12 17 0.93727 2.2 69.7AGE 0.92 18 0.92218 2.1 71. 8FAGEBIR 0.62 19 0.87833 2.0 73.9MAGEBIR 0.69 20 0.83418 1.9 75.8GRADES 0.54 21 0.81445 1.9 77.7ELEMINTR 0.21 22 0.79340 1.8 79.6SIZESIB 0.95 23 0.74599 1.7 81. 3FAMINCOM 0.39 24 0.71970 1.7 83.0BOOKSHM 0.42 25 0.71166 1.7 84.6FRDVISTS 0.27 26 0.65030 1.5 86.1SIZEHOME 0.37 27 0.60035 1.4 87.5SOCPAR 0.19 28 0.57476 1.3 88.9BIRTHORD 0.55 29 0.50849 1.2 90.1DISCIPLN 0.53 30 0.49475 1.2 91.2SOCIABLE 0.88 31 0.47246 1.1 92.3HEALTHFS 0.40 32 0.43595 1.0 93.3PDISCIPN 0.65 33 0.41587 1.0 94.3PSOCABLE 0.47 34 0.37361 0.9 95.2PHEALTHF 0.50 35 0.35041 0.8 96.0FATHEDC 0.70 36 0.32973 0.8 96.7MOTHEDC 0.59 37 0.31881 0.7 97.5SEX 0.24 38 0.25524 0.6 98.1PREGVSOK 0.25 39 0.25086 0.6 98.7DEVPVSOK 0.61 40 0.22231 0.5 99.2FJOBMOB 0.37 41 0.18665 0.4 99.6YRSEDC 0.95 42 0.12649 0.3 99.9NOFETALD 0.75 43 0.04238 0.1 100.0

TABLE 23 COMPLETE FACTOR LOADINGS FOR KOREAN GROUP

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

FATHNORC 09 04 -03 46 -04 .04 -83 -02 08 -10 -00 12 00 14 11 05FJOBSAT 07 -17 -03 12 -02 -08 -26 05 -01 06 10. 24 -18 00 11 -17NOPREG -07 20 77 -11 -02 -16 -09 -05 -18 04 06 04 35 -15 -03 05EXPNORC 11 -11 -23 17 10 16 -21 -03 25 04 -01 01 03 90 07 -18GRDVSFRD 23 10 -09 17 16 -01 17 39 -07 15 05 -20 -05 -04 24 -35READING -03 08 -05 -04 -76 05 -02 -03 01 -00 11 01 -04 00 -00 -03MATH 05 04 06 11 75 01 00 05 -04 02 01 -11 -02 06 03 -15HOMEWORK 13 03 -02 12 14 14 02 03 05 -04 -03 -08 -01 12 09 -42NURSERY 04 01 -07 11 08 04 03 60 03 -11 -01 14 -12 -09 04 -10TUTOR :",00 -06 03 14 01 12 13 16 -13 -60 05 20 -03 18 -03 08PREPSCH -02 -05 -10 14 04 00 -13 -00 08 -52 09 01 -03 11 08 -05BOOKSRD 08 -12 -08 -05 -01 17 -04 14 -02 06 00 09 03 -04 06 -40AMTTV 03 04 03 -10 07 -10 00 15 01 17 -03 -02 02 -31 -01 -10SIZECITY 14 13 -20 04 04 14 -02 28 07 -01 -09 -18 10 07 19 -05OWN HOME 15 -04 -14 09 -01 83 -01 04 00 02 -10 -04 -02 16 04 -15ROOMMATE -17 -01 15 -12 -00 -88 05 -06 -00 08 12 -12 -01 -14 -09.. 17HANDUSE -02 13 04 02 -04 -01 -08 -00 01 13 -13 -05 25 01 12 09AGE -02 -31 15 -08 -03 01 02 -08 -93 -09 04 11 -03 -11 -08 ~03

FAGEVIR 09 73 09 -02 -03 04 06 15 31 07 05 05 11 -06 02 02MAGEBIR 06 81 07 00 -10 -05 -01 -01 26 05 -01 03 08 -10 05 08GRADES 27 02 -26 17 29 14 -20 21 03 32 02 -25 -09 07 29 -45ELEMINTR -17 -07 00 12 17 01 -02 -03 -01 22 -01 11 05 -01 14 23SIZESIB -03 04 94 -06 08 -20 -10 -06 -16 08 08 02 -07 -17 -02 00FAMINCOM 02 03 -13 16 -04 16 -11 17 00 -07 -00 52 -17 01 13 -16BOOKSHM 19 12 06 57 05 06 -14 02 -10 02 -05 20 -08 10 27 -10FRDVISTS 01 07 21 08 -05 -05 11 -04 -16 -17 04 41 -04 08 02 16SIZEHOME 05 06 14 11 07 19 04 30 -09 -19 -08 26 -30 -04 -01 -28SOCPAR -01 -07 -01 24 05 -07 08 12 -23 -12 14 09 -13 -04 20 -08BIRTHORD 07 55 54 -00 11 -16 10 -03 03 -00 -01 -05 -01 -09 -01 03DISCIPLN 46 15 -10 22 15 12 -10 02 08 -01 11 -19 -07 03 55 -30SOCIABLE -18 -04 03 -12 02 -05 06 -09 01 -02 00 -14 01 -05 -91 04HEALTHS 34 24 -15 11 29 15 -00 -04 11 02 07 -21 -08 -01 32 -30PDISCIPN 78 11 -04 19 09 20 -06 04 -04 05 05 -08 01 05 14 -13PSOCABLE 56 -02 -04 16 17 06 -11 18 -01 -05 06 12 -04 10 41 -16PHEALTHF 43 08 -18 09 -07 19 07 04 -02 -26 14 34 -16 -08 21 12FATHEDC 10 -03 -06 80 15 09 -17 02 05 -08 -01 01 03 20 07 -02MOTHEDC 12 01 -25 67 09 23 -02 19 18 -21 -10 03 -17 22 12 -05SEX 02 04 08 -08 -09 -07 -12 34 -07 13 12 -02 07 -31 02 00PREGVSOK -03 -07 -15 11 02 16 06 08 02 05 -45 -06 02 03 01 01DEVPVSOK -06 02 05 -04 07 02 -12 -05 05 07 -75 03 12 01 -00 -03

, FJOBfvtOB -01 05 11 -05 02 04 -54 03 -04 -00 -08 -08 22 10 02 01I YREDC -00 -27 11 -05 03 -02 02 04 -96 -06 06 03 -00 -17 -03 02= NOFETALD 04 07 05 -02 09 04 -15 01 02 -08 -11 -12 81 06 -03 -17

TABLE 24 SUMMARY FACTOR STRUCTURE FOR KOREAN GROUP

1 2 3 4(PARRATG) (FAMLYAGE) FAMLYSIZ) (SES)

PDISCIPN .78 MAGEBIR .81 SIZESIB .94 FATHEDC .80PSOCABLE .56 FAGEBIR .73 NOPREG .77 MOTHEDC .67DISCIPLN .46 BIRTHORD .55 BIRTHORD • 54 BOOKSHM .46PHEALTHF .43 AGE -.31 FATHNORC .46HEALTHFS .34

5(READMATH)

READING -.76MATH .75

6(ROOMMATF)

ROOM~~ATE -.88O\'JNHOME • 83

7(NORCFS)

FATHNORC -.83FJOBMOB -.54

8(NURSERYF)

NURSERY .60GRDVSFRD .39SEX .34

9(YREDCAGE)

12nJEALTH)

YREDCAGEFAGEBIR

-.96-.93

.31

10(PRVATSCH)

TUTOR -.60PREPSCH -.52GRADES .32

11(DEVPPREG)

DEVPVSOK -. 75PREGVSOK -.44

FAMINCOMFRDVISTSPHEALTHF

.52

.41

.34

13 14 15 16(NFTLDPRG) (EXPNORCF) (SELFRATG) (SCHOOUJK)

NOFETALD .81 EXPNORC .90 SOCIABLE -.91 GRADES -.45NOPREG .35 SEX -.31 DISCIPLN .55 HOMEWORK -.42SIZEHO~1E -.30 AMTTV -.31 PSOCABLE .41 GRDVSFRD -.35

HEALTHFS .32 DISCIPLN -.30

Only loadings above .3 are shown.

Korean Factors

The first five factors PARRATG, FAMLYAGE, FAMLYSIZ, SES,

and READMATH are similar to the AEA and AJA structures.

Factor six, ROOMMATF (roommate factor), has two major

loadings, ROOMMATE (-.88) and OWNHOME (.83). Factor seven,

NORCFS, has the main loading on NORCFS (-.83) and a moderate

loading on FJOBMOB (-.54). NURSERYF, for nursery factor

score, has its main loading on NURSERY (.60) and low

loadings on GRDVSFRD (.39) and SEX (.34). YREDCAGE, factor

nine, shows up again. Factor ten comes from variables in the

Korean data set consisting of private schooling (PRVATSCH).

DEVPPREG is next. Factor twelve mainly loads on family

income (WEALTH). Factor 13 is NFTLDPRG and factor 14 is

EXPNORC expected NORC factor. Factors 15 and 16 are

SELFRATG and SCHOOLWK.

,<

PAGE 76

TABLE 25 CONGRUENCY COEFFICIENTS FOR AEA VERSUS KOREAN

AEA SEQUENCE KOREAN FACTOR COEFFICIENT

SES 1 PARRATG FAMLYSIZ <3,3) 90SELFRATG 2 FAMLYAGE FAMLYAGE (7,2) -84FAr~LYS IZ 3 FAMLYSIZ READMATH (5,5) -84YREDCAGE 4 SES NORCFS (15,7) -82READMATH 5 READMATH SES (1,4) 81MOOD 6 ROOMMATF YREDCAGE (4,9) -80FAMLYAGE 7 NORCFS FTLDNPRG (9,13) 72SPELLMTH 8 NURSERYF DEVPPREG (14,11> -69FTLDNPRG 9 YREDCAGE ROOMMATF (12,6) 62PARRATG 10 PRVATSCHSCHOOLWK 11 DEVPPREGROOMMATF 12 WEALTHMOB ILlTY 13 NFTLDPRGDEVPPREG 14 EXPNORCFNORCFS 15 SELFRATGMAGBOOKR 16 SCHOOU'JK

CONGRUENCE COEFFICIENTS (ROWS BY COLUMNS)(AEAs BY KOREANs)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 23 24 -12 81 09 28 -47 37 08 -31 -02 38 -15 40 22 -272 26 13 09 -09 -14 -04 01 -22 12 05 01 -12 09 -07 38 103 -03 28 90 -03 12 -42 -08 -08 -08 08 02 04 12 -33 -01 054 -03 -25 03 04 -09 07 -06 03 -80 -25 08 16 00 -11 -02 -045 01 -04 -13 -07 -84 12 -05 -02 -06 -01 09 10 03 -08 06 026 14 13 01 13 03 05 -02 -08 09 03 -03 -01 03 07 47 037 -20 -84 -18 -18 02 -04 16 -17 -23 07 -04 -13 -06 05 -08 018 -04 04 12 -27 -52 -18 09 -09 01 19 10 -02 09 -32 -12 239 01 18 50 -02 01 -11 -14 -02 -14 -03 -09 -02 72 -13 04 -09

10 03 -03 -03 -17 -22 -00 13 -24 06 09 -03 -17 06 -11 -02 2011 -10 -04 -08 18 -02 10 -19 41 -13 21 09 05 -06 -10 21 -4012 17 12 03 40 18 62 -21 42 -05 -27 -12 51 -25 19 14 -4013 -30 -47 -00 -29 10 -18 21 -17 -02 36 01 -10 -03 -19 -11 0714 -03 06 37 -04 07 -14 -05 -06 -01 10 -69 -01 23 -09 07 -0315 18 25 04 56 07 15 -82 11 14 -25 -07 30 -04 33 16 -0416 11 -11 -12 39 -13 21 -20 28 -14 -01 04 28 -07 13 15 -43

TABLE 26 CONGRUENCY COEFFICIENTS FOR AJA VERSUS KOREAN

AJA SEQUENCE KOREAN FACTOR COEFFICIENT

YREDCAGE 1 PARRATG FAMLYAGE (5,2) 92MOOD 2 FAMLYAGE YREDCAGE (1,9) 87SES 3 FAMLYSIZ FAMLYSIZ (4,3) 86FAMLYSIZ 4 SES PARRATG (13,1) 84FAMLYAGE 5 READ~4ATH ACCULTRN (12,*) 80READMATH 6 ROOMMATF READMATH (6,5) 78MAGBOOKR 7 NORCFS DEVPPREG (11,11) -72SPELLMTH 8 NURSERYF SES (3,4) 70FTLDNPRG 9 YREDCAGE NORCFS (*,7) -70SELFRATG 10 PRVATSCH SELFRATG (10,**) -67DEVPPREG 11 DEVPPREG *SESACULTRTN 12 WEALTH **SCHOOLWKPARRATG 13 NFTLDPRGMOBILITY 14 EXPNORCFCTYRURAL 15 SELFRATGSOCPARFS 16 SCHOOL\!1JK

CONGRUENCE COEFFICIENTS (ROWS BY COLUMNS)(AJAs BY KOREANs)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 -06 48 -06 21 07 -07 -10 12 87 09 -13 -00 04 21 -00 -012 21 -05 -14 -23 -05 -02 17 -03 -06 -12 06 -18 -11 -08 -28 -123 09 07 -01 70 -03 22 -70 17 11 -34 -10 41 -08 42 14 -094 -15 25 86 -13 10 -60 -07 -19 -05 14 07 -03 24 -32 -12 205 18 92 32 -06 -00 -08 -04 13 35 22 05 -05 12 -25 03 -056 00 -00 10 02 78 -11 15 -09 10 -11 -15 -12 -00 15 -01 057 -28 08 20 -38 10 -23 29 -25 11 -02 -15 -12 05 -14 -26 548 11 03 -20 36 37 24 -09 22 17 -23 -06 01 -26 30 10 -349 04 16 35 20 10 13 -23 15 05 -13 -15 12 49 08 06 -19

10 61 11 -18 31 35 29 -15 44 03 13 14 -21 -21 04 25 -6711 -05 -05 02 18 12 19 -02 09 06 -13 -72 08 02 05 -05 -0712 -47 -10 11 -80 -14 -40 39 -35 -01 07 01 -20 19 -35 -52 4913 84 08 -02 28 30 29 -16 32 -17 02 14 -04 -18 10 33 -5514 22 42 -30 12 01 05 -13 10 40 -08 -10 -20 03 18 07 -1615 28 24 16 27 13 18 -17 57 12 -06 05 28 -24 -02 23 -3516 44 -08 -26 54 14 23 -33 37 -14 06 17 -04 -17 21 39 -40

Second order structure

The second order factor dimensions are shown in the

following series of tables. They show broad areas within the

envi ronment.

TABLE 27COMMUNALITIES AND EIGENVALUES FOR AEA SECOND ORDER STRUCTURE


SES 0.89 1 2.20602 13.8 13.8SELFRATG 0.45 2 1.69954 10.6 24.4FAMLYSIZ 0.38 3 1. 54626 9.7 34.1YREDCAGE 0.19 4 1.42084 8.9 43.0READMATH 0.69 5 1. 34949 8.4 51.4MOOD 0.16 6 1.16147 7.3 58.6FAMLYAGE 0.25 7 0.92550 5.8 64.4SPELLMTH 0.18 8 0.83209 5.2 69.6FTLDNPRG 0.17 9 0.80527 5.0 t«, 7PARRATG 0.43 10 0.75090 4.7 79.4SCHOOLWK 0.25 11 0.70475 4.4 83.8SIZHOMEF 0.13 12 0.62875 3.9 87.7MOBILITY 0.88 13 0.57832 3.6 91.3DEVPPREG 0.32 14 0.53649 3.4 94.7FNORCFS 0.28 15 0.50170 3.1 97.8MAGBOOKR 0.39 16 0.35251 2.2 100.0

TABLE 28COMPLETE FACTOR LOADINGS FOR THE AEA SECOND ORDER STRUCTURE

1 2 3 4 5 6

SES 92 -26 -08 -02 -13 21SELFRATG -19 -10 16 16 58 -28FAMLYSIZ 05 -02 02 58 -06 -19YREDCAGE 09 -08 02 -03 -15 40READMATH 01 -03 78 -03 07 25MOOD 04 04 -14 00 36 04FAMLYAGE -16 45 -08 01 16 07SPELLMTH -10 00 39 05 -06 -12FTLDNPRG 02 -01 05 38 01 14PARRATG -20 04 08 -02 64 -14SCHOOLWK 24 17 15 -02 -34 30SIZEHOMEF 33 06 -10 04 -16 07MOBILITY -09 87 06 03 -13 -20DEVPPREG -01 08 -02 56 08 -03FNORCFS 38 -24 -02 -02 03 -25MAGBOOKR 40 31 04 10 -01 41

TABLE 29 SUMMARY OF AEA SECOND ORDER FACTOR STRUCTURE

1 2 3

SES .92 MOBILITY -.87 READMATH .78Iv1AGBOOKR .40 FAMLYAGE .45 SPELLMTH .39FNORCFS .38 SES -.25ROOMMATF .33

4 5 6

FAMLYSIZ .58 PARRATG .64 YREDCAGE .40DEVPPREG .56 SELFRATG .58 SCHOOUvK .30FTLDNPRG .38 MOOD .36 SELFRATG -.28

SCHOOUvK -.34 READMATH .25FNORCFS -.25


The first three second order factors center on the

factors of SES, MOBILITY, and READMATH. Factor four shows

the relationship of FAMLYSIZ, DEVPPREG, and FTLDNPRG. Factor

five reflects the adjective check list data, and factor six

a combination of school related activities.

TABLE 30COMMUNALITIES AND EIGENVALUES FOR AJA SECOND ORDER STRUCTURE


YREDCAGE 0.46 1 2.00953 12.6 12.6MOOD 0.13 2 1.57886 9.9 22.4SES 0.24 3 1.47641 9.2 31. 7FAMLYSIZ 0.32 4 1. 31337 8.2 39.9FAMLYAGE 0.45 5 1. 25924 7.9 47.7READMATH 0.68 6 1.11243 7.0 54.7MAGBOOKR 0.18 7 1. 03440 6.5 61.2SPELLMTH 0.14 8 0.98007 6.1 67.3PTLDNPRG 0.17 9 0.84130 5.3 72.5SELFRATG 0.52 10 0~77734 4.9 77.4DEVPPREG 0.03 11 0.72962 4.6 82.0ACULTRTN 0.52 12 0.67598 4.2 86.2PARRATG 0.41 13 0.62488 3.9 90.1MOBILITY 0.29 14 0.57502 3.6 93.7CTYRURAL 0.13 15 0.53166 3.3 97.0SOCPARFS 0.25 16 0.47980 3.0 100.0

TABLE 31COMPLETE FACTOR LOADINGS FOR THE AJA SECOND ORDER STRUCTURE

1 2 3 4 5 6

YREDCAGE -14 63 03 -06 02 -22MOOD 17 06 27 09 -11 -04SES 05 29 -111 05 08 07FAMLYSIZ -12 14 05 -08 50 -21FAMLYAGE 05 10 04 05 04 -66READMATH -05 08 07 -81 -04 02MAGBOOKR -24 -12 20 -28 02 -20SPELLMTH 10 24 -06 -16 -18 13PTLDNPRG 00 05 -19 -04 38 -02SELFRATG 70 17 -06 00 -10 10PREGDEVP 04 -03 -11 -13 03 00ACULTRTN -22 -11 71 -04 -04 -05PARRATG 61 -07 -08 02 02 -04MOBI L1TY -04 19 03 -15 -41 -25CTYRURAL 12 31 -09 09 11 02

TABLE 32 SUMMARY OF AJA SECOND ORDER FACTOR STRUCTURE

1 2 3

SELFRATG • 70 YREDCAGE .63 ACULTRTN .71PARRATG .61 CTYRURAL .31 SES -.41SOCPARFS .39 SES .29 SOCPARFS -.34

MOOD .26

4 5 6

READMATH -.81 FAMLYSIZ .50 FAMLYAGE -.65MAGBOOKR -.28 MOBILITY -.41 MOBILITY -.25

FTLDNPRG .38

* Only loadings above .25 shown.

Factor one is the adjective check list data. Factor two,

three, and four center on YREDCAGE, ACCULTRN, and READMATH.

Factor five is a combination of FAMLYSIZ, MOBILITY, and

FTLDNPRG. ~actor six centers on FAMLYAGE.

TABLE 33COMMUNALITIES AND EIGENVALUES FOR KOREAN SECOND ORDER STRUCTURE


PARRATG 0.64 1 2.03695 12.7 12.7FAMLYAGE 0.80 2 1. 59720 10.0 22.7FAMLYSIZ 0.17 3 1.40373 8.8 31. 5SES 0.65 4 1. 26722 7.9 39.4READMATH 0.12 5 1.18203 7.4 46.8ROOMMATF 0.39 6 1.08881 6.8 53.6NORCFS 0.07 7 1.03713 6.5 60.1NURSERYF 0.64 8 1.01635 6.4 66.4YREDCAGE 0.13 9 0.93613 5.9 72.3PRVATSCH 0.11 10 0.89204 5.6 77.9DEVPPREG 0.13 11 0.70958 4.4 82.3WEALTH 0.53 12 0.65138 4.1 86.4NFTLDPRG 0.11 13 0.62848 3.9 90.3EXPNORCF 0.21 14 0.57550 3.6 93.9SELFRATG 0.19 15 0.52254 3.3 97.2SCHOOLWK 0.25 16 0.45481 2.8 100.0

TABLE 34COMPLETE FACTOR LOADINGS FOR KOREAN SECOND ORDER STRUCTURE

1 2 3 4 5 6

PARRATG 78 04 05 -07 11 -22FAMLYAGE 10 12 86 09 10 -Ol~

FAMLYSIZ -05 -09 -05 38 06 09PARNTEDC 15 -16 -05 18 06 -79READMATH 05 23 -06 -02 07 -22ROOMMATF 22 -15 03 -58 01 08NORCFS -02 -02 -01 -06 02 26NURSERYF -07 -07 05 -18 80 -09YREDCAGE -00 07 25 -18 -07 03PRVATSCH 09 25 06 09 05 12DEVPPREG 17 -06 -08 28 01 -01WEALTH 01 -74 02 04 05 01NFTLDPRG -13 22 15 -04 -04 00EXPNORC 02 -07 -02 -25 -31 -19SELFRATG 25 -02 08 -02 11 -25SCHOOLWK -32 -21 08 19 -14 03

TABLE 35 SUMMARY OF KOREAN SECOND ORDER FACTOR STRUCTURE

1 2 3

PARRATG .78 WEALTH -.73 FAMLYAGE .86SCHOOLWK -.38 PRVATSCH .27 YREDCAGE .29SELFRATG .33

4 5 6

ROOMMATF -.57 NURSERYF .77 SES -.79FAMLYSIZ .38 EXPNORCF -.31 SELFRATG -.31DEVPPREG .29 SCHOOU<JK -.26 NORCFS .25

* Only loadings above .25 shown.

The Korean structure differs more from the first two

structures, probably resulting from the differences in the

original variables, but it still shows similarities. The

second order factors center on PARRATG, WEALTH, FAMLYAGE,

NURSERYF, SES, and a combination of ROOMMATF and FAMLYSIZ.

Four second order factors show up cross-culturally:

socio-economic status, parental and self ratings, family

size, and family age.

Stepwise Multiple Regression (SMR)

The following tables show the stepwise multiple

regression analyses using the environmental variables as

predictors and the cognitive abilities as criterion. The

analyses are shown in entirety so that the simple

correlations of the variables with criterion might also be

shown.

TABLE 36 SMR WITH EQ VARIABLES PREDICTING AEA VERBAL ABILITY

VARIABLE MULTIPLE R R SQUARE RSQ CHANGE SIMPLE R

GRADES 0.25922 0.06720 0.06720 0.25922BOOKSRD 0.33756 0.11395 0.04675 0.25677SOCPAR 0.36329 0.13198 0.01804 0.21584BOOKSHM 0.38297 0.14667 0.01469 0.20316FRDVISTS 0.39433 0.15549 0.00883 -0.06200FRNDLANG 0.40530 0.16427 0.00878 0.18343DEVPPROB 0.41520 0.17239 0.00812 -0.11367PSCHOLAR 0.42311 0.17902 0.00663 -0.20279READING 0.43110 0.18585 0.00683 0.14429NURSERY 0.43733 0.19125 0.00540 0.11372GRVSFRD 0.44252 0.19582 0.00457 0.15277SIZECITY 0.44802 0.20072 0.00490 0.06850FYREDC 0.45166 0.20399 0.00328 0.16895TEMPERMT 0.45441 0.20649 0.00250 0.00359ANXIETY 0.45625 0.20816 0.00167 -0.06802SEX 0.45839 0.21012 0.00196 0'.06950MAG READ 0.45955 0.21118 0.00107 0.11657SIZEHOME 0.46067 0.21221 0.00103 -0.01175FAMINCOM 0.46170 0.21317 0.00096 0.13532SIZESIB 0.46254 0.21394 0.00077 -0.02176NOPREG 0.46491 0.21614 0.00220 -0.03579ROOMMATE 0.46618 0.21732 0.00118 -0.04798BI RTHORD 0.46742 0.21848 0.00115 -0.05145NOFETALD 0.46839 0.21939 0.00091 0.01357SCHOLAR 0.46919 0.22014 0.00075 -0.10527ELEMINTR 0.46992 0.22082 0.00068 -0.02434FJOBMOB 0.47050 0.22137 0.00055 0.01151FNORC 0.47150 0.22231 0.00094 0.08654HANDWRIT 0.47204 0.22282 0.00051 0.00624FAGEBIR 0.47253 0.22329 0.00046 0.07453MATH 0.47284 0.22358 0.00029 -0.05722SPELLING 0.47329 0.22401 0.00043 -0.05589YRSEDC 0.47373 0.22442 0.00042 0.06892AGE 0.47421 0.22488 0.00046 0.05503PTEMPERM 0.47445 0.22510 0.00022 0.07728HOSTILTY 0.47465 0.22529 0.00019 -0.05383HOMEWORK 0.47483 0.22546 0.00017 0.12893AMTTV 0.47496 0.22559 0.00012 -0.09111DEPRESS 0.47508 0.22570 0.00012 -0.04122JOB 0.47518 0.22580 0.00010 0.01570MYREDC 0.47526 0.22587 0.00008 0.14079MAGEBIR 0.47533 0.22594 0.00006 0.05322FATHM~AY 0.47535 0.22596 0.00002 -0.04069PREGPROB 0.47536 0.22597 0.00001 -0.01888PIDGIN -0.07116

TABLE 37 SMR WITH EQ VARIABLES PREDICTING AEA SPATIAL ABILITY


PSCHOLAR 0.15782 0.02491 0.02491 -0.15782SPELLING 0.21131 0.04465 0.01974 -0.15176BOOKSHM 0.24710 0.06106 0.01641 0.14487DEVPPROB 0.26639 0.07096 0.00991 -0.10696SOCPAR 0.28023 0.07853 0.00757 0.12622MATH 0.29502 0.08703 0.00850 0.15368FAGEBIR 0.30730 0.09443 0.00740 0.11028FRDVISTS 0.31589 0.09979 0.00535 -0.04206NURSERY 0.32368 0.10477 0.00499 0.10921AGE 0.33127 0.10974 0.00497 0.08797YRSEDC 0.33715 0.11367 0.00393 0.04979DEPRESS 0.34239 0.11723 0.00356 -0.08424PIDGIN 0.34628 0.11991 0.00267 -0.08327SEX 0.34946 0.12212 0.00221 0.04907MAG READ 0.35260 0.12433 0.00220 0.05431SIZECITY 0.35516 0.12614 0.00181 0.05648SCHOLAR 0.35765 0.12792 0.00178 -0.07720ROOMMATE 0.35971 0.12939 0.00147 -0.05711FYREDC 0.36145 0.13064 0.00126 0.11983FRNDLANG 0.36294 0.13172 0.00108 0.08961BIRTHORD 0.36441 0.13279 0.00107 0.03974NOPREG 0.36638 0.13423 0.00144 -0.03981SIZESIB 0.37061 0.13735 0.00312 -0.00224NOFETALD 0.37306 0.13917 0.00182 -0.01291PREGPROB 0.37478 0.14046 0.00060 -0.01075READING 0.37556 0.14105 0.00059 -0.00614GRADES 0.37612 0.14146 0.00041 0.13897HOSTILTY 0.37640 0.14168 0.00022 -0.07957FJOBMOB 0.37669 0.14190 0.00022 0.01482FNORC 0.37727 0.14233 0.00044 0.08922FAfvllNCOM 0.37753 0.14253 0.00019 0.11402MYREDC 0.37771 0.14267 0.00014 0.09664ELEMINTR 0.37790 0.14281 0.00014 -0.06077HOMEWORK 0.37806 0.14293 0.00012 0.06551BOOKSRD 0.37819 0.14303 0.00010 0.03398FATHAWAY 0.37829 0.14311 0.00008 -0.03578AMTTV 0.37837 0.14316 0.00006 -0.03993SIZEHOME 0.37844 0.14322 0.00005 0.01321MAGEBIR 0.37848 0.14325 0.00003 0.08169GRVSFRD 0.37852 0.14328 0.00003 0.05169PTEMPERM 0.37853 0.14329 0.00001 0.10947ANXIETY -0.08029HANDlI/RI T 0.02929JOB 0.01328TEMPERMT 0.04455

TABLE 38 SMR WITH EQ VARIABLES PREDICTING AEA PERCEPTUAL SPEED


GRADES 0.27174 0.07384 0.07384 0.27174DEVPPROB 0.30565 0.09342 0.01958 -0.16477PSCHOLAR 0.33084 0.10946 0.01604 -0.23346SOCPAR 0.34308 0.11771 0.00825 0.15742FRDVISTS 0.35360 0.12503 0.00733 -0.07129NURSERY 0.36152 0.13069 0.00566 0.10133MATH 0.36881 0.13602 0.00533 0.09961MAGREAD 0.37641 0.14169 0.00566 0.08523NOPREG 0.38085 0.14504 0.00336 -0.08879SIZESIB 0.38538 0.14852 0.00347 -0.03736MYREDC 0.38949 0.15170 0.00318 0.00813ELEMINTR 0.39418 0.15538 0.00368 -0.05536SEX 0.39745 0.15796 0.00259 0.09143FAMINCOM 0.39976 0.15981 0.00185 0.07684FNORC 0.40210 0.16169 0.00188 0.01204MAGEBIR 0.40403 0.16324 0.00155 -0.01462DEPRESS 0.40561 0.16452 0.00128 -0.08067BOOKSRD 0.40731 0.16590 0.00138 0.08914FATHAWAY 0.40878 0.16710 0.00120 0.02602SIZECITY 0.41027 0.16832 0.00122 0.02742NOFETALD 0.41160 0.16941 0.00109 -0.05420PIDGIN 0.41278 0.17039 0.00098 -0.08868ROOMMATE 0.41379 0.17122 0.00083 -0.07317GRVSFRD 0.41472 0.17199 0.00077 0.11135HANm~RIT 0.41548 0.17262 0.00063 0.04479PTEMPERM 0.41614 0.17317 0.00055 0.10617JOB 0.41677 0.17369 0.00052 -0.01645FRNDLANG 0.41745 0.17426 0.00057 0.10711PREGPROB 0.41795 0.17469 0.00043 -0.03908SIZEHOME 0.41847 0.17512 0.00043 0.00284FAGEBIR 0.41896 0.17552 0.00041 0.01846SCHOLAR 0.41937 0.17587 0.00034 -0.16222AMTTV 0.41976 0.17620 0.00033 -0.03762BIRTHORD 0.42003 0.17642 0.00022 -0.01873FJOBMOB 0.42025 0.17661 0.00019 -0.00384SPELLING 0.42046 0.17679 0.00017 -0.02786READING 0.42068 0.17697 0.00019 -0.02205HOt4EWORK 0.42079 0.17707 0.00009 0.11515TEMPERMT 0.42089 0.17715 0.00008 0.07815YRSEDC 0.42097 0.17721 0.00006 0.04885HOSTILTY 0.42104 0.17728 0.00006 -0.07436BOOKSHM 0.42110 0.17732 0.00005 0.03598FYREDC 0.42112 0.17734 0.00002 0.03806AGE 0.03994ANXIETY -0.06761

TABLE 39 SMR WITH EQ VARIABLES PREDICTING AEA MEMORY


GRADES 0.10389 0.01079 0.01079 0.10389HOSTILTY 0.13077 0.01710 0.00631 -0.09024MAGREAD 0.14553 0.02118 0.00408 0.07056FRDVISTS 0.15986 0.02556 0.00438 -0.06071PTEMPERM 0.17353 0.03011 0.00456 0.09640SIZECITY 0.18487 0.03418 0.00406 0.05516BIRTHORD 0.19254 0.03707 0.00290 0.04631AGE 0.20073 0.04029 0.00322 0.06772PIDGIN 0.20676 0.04275 0.00246 -0.06247NURSERY 0.21220 0.04503 0.00228 0.05948SOCPAR 0.21559 0.04648 0.00145 0.06628TEMPERMT 0.21882 0.04788 0.00140 0.01822DEVPPROB 0.22167 0.04914 0.00126 -0.05177JOB 0.22483 0.05055 0.00141 0.05589MAGEBIR 0.22741 0.05172 0.00117 0.01800FAMINCOM 0.23023 0.05301 0.00129 0.06487PREGPROB 0.23266 0.05413 0.00112 0.02186NOPREG 0.23526 0.05535 0.00122 -0.01258SIZESIB 0.24116 0.05816 0.00281 0.02717SPELLI NG 0.24325 0.05917 0.00101 -0.04932NOFETALD 0.24533 0.06019 0.00101 -0.01383MYREDC 0.24675 0.06089 0.00070 0.01094 ...t

BOOKSHM 0.24864 0.06182 0.00093 0.05667BOOKSRD 0.24976 0.06238 0.00056 0.05378ELEMINTR 0.25056 0.06278 0.00040 -0.04786HANDWRIT 0.25141 0.06321 0.00042 -0.01600SCHOLAR 0.25227 0.06364 0.00043 -0.03847GRVSFRD 0.25330 0.06416 0.00052 0.04438DEPRESS 0.25410 0.06457 0.00041 -0.07313FNORC 0.25466 0.06485 0.00028 0.02803PSCHOLAR 0.25513 0.06509 0.00024 -0.09903HOMEWORK 0.25558 0.06532 0.00023 0.03553FAGEBIR 0.25600 0.06553 0.00021 0.03916MATH 0.25638 0.06573 0.00020 0.02112FRNDLANG 0.25675 0.06592 0.00019 0.06145FATHAWAY 0.25706 0.06608 0.00016 -0.00906YRSEDC 0.25735 0.06623 0.00015 0.06160SIZEHOME 0.25763 0.06637 0.00014 0.01381ANXIETY 0.25791 0.06652 0.00015 -0.06618READING 0.25811 0.06662 0.00010 0.03096FYREDC 0.25819 0.06666 0.00004 0.03420AMTTV 0.25826 0.06670 0.00004 -0.02468FJOBMOB 0.25828 0.06671 0.00001 -0.00414ROOMMATE -0.01032SEX 0.02965

TABLE 40 SMR WITH EQ VARIABLES PREDICTING AEA SPEARMAN'S 'G'


GRADES 0.31336 0.09820 0.09820 0.31336BOOKSHM 0.35238 0.12417 0.02597 0.20909PSCHOLAR 0.38647 0.14936 0.02519 -0.27498SOCPAR 0.40803 0.16648 0.01713 0.22906DEVPPROB 0.42652 0.18192 0.01544 -0.15700BOOKSRD 0.43793 0.19178 0.00986 0.19254NURSERY 0.44860 0.20125 0.00947 0.13661FRDVISTS 0.45765 0.20944 0.00820 -0.05416FAMINCOM 0.46451 0.21577 0.00632 0.16328SPELLI NG 0.46977 0.22068 0.00492 -0.09923FRNDLANG 0.471~96 0.22558 0.00490 0.18460SIZECITY 0.47841 0.22887 0.00329 0.05989ANXIETY 0.48097 0.23133 0.00245 -0.10211GRVSFRD 0.48292 0.23322 0.00189 0.15065SCHOLAR 0.48493 0.23515 0.00194 -0.15398PIDGIN 0.48655 0.23673 0.00158 -0.11112FYREDC 0.48812 0.23826 0.00152 0.18121MATH 0.48963 0.23973 0.00147 0.06280READING 0.49176 0.24182 0.00209 0.07562FAGEBIR 0.49296 0.24301 0.00118 0.10695MAG READ 0.49410 0.24413 0.00112 0.09646NOFETALD 0.49504 0.24507 0.00093 -0.00572AGE 0.49602 0.24604 0.00097 0.08047YRSEDC 0.49743 0.24744 0.00140 0.08335SIZESIB 0.49807 0.24807 0.00063 -0.01765NOPREG 0.50279 0.25279 0.00472 -0.04854ROOMMATE 0.50343 0.25345 0.00065 -0.06641PREGPROB 0.50403 0.25404 0.00060 -0.01764JOB 0.50461 0.25464 0.00059 0.00350FNORC 0.50510 0.25513 0.00049 0.10764FJOBMOB 0.50615 0.25619 0.00106 0.01336DEPRESS 0.50651 0.25655 0.00037 -0.08401ELEMINTR 0.50679 0.25683 0.00028 -0.03816SEX 0.50699 0.25704 0.00021 0.10753BIRTHORD 0.50715 0.25720 0.00016 -0.00979SIZEHOME 0.50735 0.25740 0.00020 0.02231HOME\~ORK 0.50743 0.25748 0.00009 0.13046PTEMPERM 0.50751 0.25757 0.00009 0.14118HANDWRIT 0.50759 0.25765 0.00008 0.03095HOSTILTY 0.50767 0.25773 0.00008 -0.10258MYREDC 0.50770 0.25776 0.00002 0.15742AMTTV 0.50772 0.25778 0.00002 -0.08188TEMPERMT 0.50773 0.25779 0.00002 0.06173MAGEBIR 0.50775 0.25781 0.00001 0.07621FATHAWAY -0.04669

TABLE 41SMR WITH EQ FACTOR SCORES PREDICTING AEA VERBAL ABILITY


SCHOOLWK 0.30760 0.09462 0.09462 0.30760MAGBOOKR 0.37575 0.14119 0.04657 0.26921SES 0.39852 0.15882 0.01763 0.25200DEVPPREG 0.40381 0.16306 0.00424 -0.07720PARRATG 0.40872 0.16705 0.00399 -0.15767READMATH 0.41161 0.16942 0.00237 0.10820SPELLMTH 0.41292 0.17050 0.00108 -0.03298MOOD 0.41418 0.17155 0.00104 -0.03485MOB IL1TY 0.41509 0.17230 0.00076 -0.01134ROOMMATF 0.41573 0.17283 0.00053 0.07369FNORCFS 0.41627 0.17328 0.00044 0.01210SELFRATG 0.41664 0.17359 0.00031 -0.12202FTLDNPRG 0.41698 0.17388 0.00029 0.00458YREDCAGE 0.41721 0.17407 0.00019 0.10683FAMLYAGE 0.41728 0.17412 0.00006 -0.02960FAMLYSIZ -0.03107

TABLE 42SMR WITH EQ FACTOR SCORES PREDICTING AEA SPATIAL ABILITY


SPELLMTH 0.17101 0.02925 0.02925 -0.17101PARRATG 0.22444 0.05037 0.02113 -0.15623SES 0.25474 0.06489 0.01452 0.16306DEVPPREG 0.27079 0.07333 0.00844 -0.10062SCHOOLWK 0.28153 0.07926 0.00593 0.12425MOOD 0.28775 0.08280 0.00354 -0.06450FAMLYAGE 0.29099 0.08467 0.00187 -0.08055MAGBOOKR 0.29478 0.08690 0.00222 0.09040READMATH 0.29856 0.08914 0.00224 -0.06139YREDCAGE 0.30046 0.09028 0.00114 0.07897SELFRATG 0.30273 0.09165 0.00137 -0.08732FTLDNPRG 0.30433 0.09262 0.00097 -0.03650FAMLYSIZ 0.30539 0.09326 0.00064 -0.01075MOBILITY 0.30628 0.09381 0.00055 -0.05723RODt4MATF 0.30633 0.09384 0.00003 0.06907FNORCFS 0.04364

TABLE 43SMR WITH EQ FACTOR SCORES PREDICTING AEA PERCEPTUAL SPEED

VARIABLE MULTI PLE R R SQUARE RSQ CHANGE SIMPLE R

SCHOOLWK 0.23973 0.05747 0.05747 0.23973DEVPPREG 0.27961 0.07818 0.02071 -0.16038PARRATG 0.30555 0.09336 0.01518 -0.18103READMATH 0.32028 0.10258 0.00922 -0.07290MAGBOOKR 0.33778 0.11409 0.01152 0.12552SPELLMTH 0.34247 0.11729 0.00319 -0.08123MOOD 0.34731 0.12062 0.00334 -0.05872FTLDNPRG 0.35125 0.12337 0.00275 -0.07302SES 0.35282 0.12448 0.00111 0.07308MOBILITY 0.35370 0.12510 0.00062 0.03595ROOMMATF 0.35444 0.12563 0.00052 0.08041SELFRATG 0.35510 0.12610 0.00047 -0.16846FAMLYAGE 0.35546 0.12635 0.00025 0.00666YREDCAGE 0.35572 0.12654 0.00019 0.07314FNORCFS 0.35587 0.12665 0.00011 -0.01070FAMLYSIZ 0.35589 0.12666 0.00001 -0.04826

TABLE 44 SMR WITH EQ FACTOR SCORES PREDICTING AEA MEMORY

VARIABLE MULTIPLE R R SQUARE RSQ CHANGE S Ir'1PLE R

PARRATG 0.11836 0.01401 0.01401 -0.11836MAGBOOKR 0.14218 0.02022 0.00621 0.08483YREDCAGE 0.15385 0.02367 0.00345 0.08272MOOD 0.16200 0.02624 0.00257 -0.06819DEVPPREG 0.16650 0.02772 0.00148 -0.03769SCHOOUJK 0.16994 0.02888 0.00116 0.08305SELFRATG 0.17360 0.03014 0.00125 -0.04542SPELLMTH 0.17691 0.03130 0.00116 -0.03559FAMLYSIZ 0.18000 0.03240 0.00110 0.01971FTLDNPRG 0.18352 0.03368 0.00128 -0.02462MOBILITY 0.18653 0.03479 0.00111 -0.02542SES 0.18677 0.03488 0.00009 0.05811FNORCFS 0.18715 0.03503 0.00014 0.01544FAMLYAGE 0.18723 0.03506 0.00003 -0.02761ROOMt4ATF 0.18732 0.03509 0.00003 0.03447READMATH 0.18737 0.03511 0.00002 0.01338

TABLE 45SMR WITH EQ FACTORS SCORES PREDICTING AEA SPEARMAN'S 'G'


SCHOOLWK 0.32247 0.10399 0.10399 0.32247SES 0.38241 0.14624 0.04225 0.26746PARRATG 0.40510 0.16411 0.01787 -0.23681MAGBOOKR 0.42335 0.17922 0.01512 0.23216DEVPPREG 0.43784 0.19170 0.01248 -0.12934SPELLMTH 0.44900 0.20160 0.00990 -0.11588MOOD 0.45363 0.20578 0.00417 -0.07233YREDCAGE 0.45453 0.20660 0.00082 0.12288FTLDNPRG 0.45540 0.20739 0.00079 -0.02383READf'.1ATH 0.45597 0.20791 0.00052 0.01237MOBI LlTY 0.45660 0.20849 0.00058 -0.01664SELFRATG 0.45705 0.20890 0.00041 -0.17173FAMLYSIZ 0.45733 0.20915 0.00025 -0.02829FAMLYAGE 0.45752 0.20932 0.00018 -0.06105FNORCFS 0.45767 0.20946 0.00014 0.03094ROOMMATF 0.45769 0.20948 0.00002 0.11511

A summary table of all the previous regression tables is

presented. Only those variables which accounted for at least

one additional percent of variance are included. The (*)

signifies the variables appear in more than one list.

TABLE 46 SUMMARY OF SMR TABLES FOR AEAs

SMR's USING 16 FACTOR SCORES AS PREDICTORS

VERBSE

SCHOOLWK*MAGBOOKR*SES* 15.9%

TOTAL VARIANCE 17.4%

MEMSE

PARRATG*

TOTAL VARIANCE

SPATSE PERSPDSE------ -------SPELLMTH SCHOOU'IK*PARRATG* DEVPPREGSES* 6.5% PARRATG* 9.3%

9.4% 12.7%

SPEAR'G'-------

1.4% SCHOOUJK*SES*PARRATG*MAGBOOKR*DEVPPREG* 19.2%

3.5% 20.9%

SMR's USING ORGINIAL 45 EQ VARIABLES

VERBSE SPATSE PERSPDSE------ ------ -------GRADES* PSCHOLAR GRADES*BOOKSRD SPELLI NG DEVPROB*SOCPAR* BOOKSHM* PSCHOLAR 10.9%BOOKSHM* 14.7% DEVPPROB* 7.1%

TOTAL VARIANCE 22.6% 14.3% 17.7%

MEMSE SPEAR'G'----- -------GRADES* 1.1% GRADES*

BOOKSHM*SOCPAR*DEVPPROB* 18.2%

TOTAL VARIANCE 6.7% 25.8%

Variables appearing in more than one list.

PARRATG (4)SCHOOLWK (3)MAGBOOKR (2)SES (2)

GRADES (4)BOOKSHM (3)DEVPPROB (3)SOCPAR (2)

The first thing to notice is the amount of variance that

all 45 variables predict for each cognitive factor. This is

respectively 15, 14, 18, 8, and 26 percent for verbal,

spatial, perceptual speed, memory, and Spearman's 'g'.

The dimensions important to each cognitive factor vary.

School work, amount of reading, and socio-economic status

(SES) are impo~tant to verbal rating. Math ability, parental

ratings, and SES relate to spatial ability. School work,

developmental and pregnancy problems, and parental ratings

relate to perceptual speed. Memory is weakl y rel ated to

parental ratings and grades. Spearman's 'g' is strongly

affected by environmental variables with school work, SES,

parental ratings, amount of reading and development and

pregnancy problems being important.

PARRATG, SCHOOLWK, MAGBOOKR, and SES show up as factors

important to more than one ability while GRADES, BOOKSHM,

DEVPPROB, and SOCPAR are important variables.

TABLE 47 SMR WITH EQ VARIABLES PREDICTING AJA VERBAL ABILITY


GRADES 0.20052 0.04021 0.04021 0.20052FATHM~AY 0.27768 0.07710 0.03690 -0.19459MAGREAD 0.31527 0.09940 0.02229 0.17141BOOKSHM 0.34237 0.11722 0.01782 0.18620BIRTHORD 0.35315 0.12471 0.00750 -0.05682PTEMPERM 0.36127 0.13052 0.00580 -0.05553PSCHOLAR 0.37645 0.14172 0.01120 0.11096FNORC 0.38440 0.14776 0.00604 0.16199HANDWRIT 0.39066 0.15262 0.00485 -0.05753SCHOLAR 0.39443 0.15558 0.00296 0.04463TEMPERMT 0.40126 0.16101 0.00543 0.02537FJOBMOB 0.40579 0.16467 0.00366 -0.04024SIZEHOME 0.40991 0.16802 0.00336 -0.01403NOFETALD 0.41506 0.17228 0.00L~25 0.07054S IZEC ITY 0.41869 0.17530 0.00303 0.07949PIDGIN 0.42190 0.17800 0.00269 -0.11360MAGEBIR 0.42437 0.18009 0.00210 0.05640GRVSFRD 0.42660 0.18199 0.00189 0.14587ANXIETY 0.42916 0.18418 0.00219 -0.04922HOMEWORK 0.43104 0.18580 0.00162 0.01977MYREDC 0.43305 0.18753 0.00173 0.17016AGE 0.43565 0.18979 0.00226 -0.00975YRSEDC 0.44093 0.19442 0.00462 -0.03992FRNDLANG 0.44245 0.19576 0.00135 0.04984HOSTI LTY 0.44405 0.19718 0.00142 -0.06334DEPRESS 0.44712 0.19992 0.00273 0.00400FAGEBIR 0.44884 0.20146 0.00154 0.04561SPELLING 0.45072 0.20315 0.00169 -0.04104ROOMMATE 0.45260 0.20484 0.00169 -0.01705READING 0.45431 0.20640 0.00156 0.05495BOOKSRD 0.45651 0.20840 0.00200 0.15787JOB 0.45815 0.20990 0.00150 -0.06014DEVPPROB 0.45937 0.21102 0.00112 0.00263PREGPROB 0.46140 0.21289 0.00187 -0.04094FRDVISTS 0.46258 0.21398 0.00108 0.03205FAMINCO/v1 0.46315 0.21451 0.00053 0.10779ELEMINTR 0.46357 0.21490 0.00039 -0.01009NURSERY 0.46378 0.21509 0.00020 0.05358SIZESIB 0.46386 0.21517 0.00007 -0.03860MATH 0.46390 0.21520 0.00004 -0.00773AMTTV -0.03718FYREDC 0.14439NOPREG -0.00611SEX 0.04956SOCPAR 0.06085

TABLE 48 SMR WITH EQ VARIABLES PREDICTING AJA SPATIAL ABILITY


MATH 0.18236 0.03326 0.03326 0.18236FATHMJAY 0.23441 0.05495 0.02169 -0.15333SEX 0.25442 0.06473 0.00978 0.03562MAGREAD 0.27397 0.07506 0.01033 0.08165TEMPERMT 0.28611 0.08186 0.00680 0.10295PTEMPERM 0.30198 0.09119 0.00933 -0.06553HANDWRIT 0.31350 0.09828 0.00709 -0.08005MYREDC 0.32394 0.10494 0.00666 0.10471PSCHOLAR 0.33232 0.11044 0.00550 0.02928SCHOLAR 0.34084 0.11617 0.00573 0.04999FRDVISTS 0.34670 0.12020 0.00403 0.04736SIZEHOME 0.35295 0.12457 0.00437 -0.02082SPELLING 0.35895 0.12885 0.00427 -0.14005FJOBMOB 0.36257 0.13146 0.00261 -0.07361FAGEBIR 0.36627 0.13415 0.00270 0.08528AGE 0.37033 0.13714 0.00299 -0.02365YRSEDC 0.37947 0.14400 0.00685 -0.06230FYREDC 0.38359 0.14714 0.00314 0.06777HOSTI LTY 0.38810 0.15062 0.00348 -0.07046NURSERY 0.39107 0.15294 0.00232 0.09259ROOMMATE 0.39379 0.15507 0.00213 0.04539DEPRESS 0.39644 0.15716 0.00209 -0.02379SIZESIB 0.39854 0.15884 0.00167 -0.01369PIDGIN 0.40062 0.16050 0.00166 -0.01579HOME\~ORK 0.40278 0.16223 0.00174 -0.00816DEVPPROB 0.40383 0.16308 0.00085 -0.01703NOPREG 0.40467 0.16376 0.00068 -0.00209BOOKSHM 0.40549 0.16442 0.00066 0.07172BOOKSRD 0.40632 0.16510 0.00068 0.00946FRNDLANG 0.40681 0.16550 0.00040 0.02414ANXIETY 0.40739 0.16597 0.00047 -0.04882GRADES 0.40770 0.16622 0.00025 0.07976JOB 0.40797 0.16644 0.00023 -0.06547SIZECITY 0.40819 0.16662 0.00018 0.04525AMTTV 0.40843 0.16681 0.00019 -0.02594GRVSFRD 0.40864 0.16699 0.00018 0.03908PREGPROB 0.40874 0.16707 0.00008 -0.01764ELEMINTR 0.40883 0.16714 0.00007 -0.03430FNORC 0.40892 0.16722 0.00007 0.06316SOCPAR 0.40898 0.16727 0.00005 0.03848READING 0.40904 0.16732 0.00005 -0.03919MAGEBIR 0.40907 0.16734 0.00003 0.05546BIRTHORD 0.02018FAMINCOM 0.10779NOFETALD 0.01163

TABLE 49 SMR WITH EQ VARIABLES PREDICTING AJA PERCEPTUAL SPEED


TEMPERMT 0.15851 0.02513 0.02513 0.15851MATH 0.21395 0.04577 0.02065 0.14880PTEMPERM 0.24348 0.05928 0.01351 -0.05145PSCHOLAR 0.30264 0.09159 0.03231 0.09616FATHAWAY 0.31897 0.10174 0.01015 -0.11473DEVPPROB 0.33143 0.10985 0.00810 -0.10362MAGEBIR 0.34085 0.11618 0.00633 0.11192SIZEHOME 0.35034 0.12274 0.00656 -0.05096SIZECITY 0.35835 0.12842 0.00568 0.09109AMTTV 0.36715 0.13480 0.00638 -0.05517HOMEWORK 0.37397 0.13986 0.00506 -0.04200ANXIETY 0.37959 0.14409 0.00423 -0.09833GRADES 0.38570 0.14877 0.00468 0.14567READING 0.39010 0.15218 0.00341 -0.11002NURSERY 0.39324 0.15464 0.00246 0.09973JOB 0.39589 0.15673 0.00209 0.00052ROOMMATE 0.39858 0.15887 0.00214 0.04746SEX 0.40119 0.16096 0.00209 0.05297MAGREAD 0.40405 0.16326 0.00230 0.04199SOCPAR 0.40729 0.16588 0.00262 -0.00857SCHOLAR 0.41017 0.16824 0.00236 0.12750NOPREG 0.41234 0.17002 0.00178 -0.03084MYREDC 0.41388 0.17130 0.00127 0.01889PIDGIN 0.41523 0.17241 0.00112 0.07698AGE 0.41648 0.17345 0.00104 -0.02305YRSEDC 0.42434 0.18006 0.00661 -0.05845DEPRESS 0.42497 0.18060 0.00054 -0.07223FAMINCOM 0.42535 0.18092 0.00032 0.03395FNORC 0.42622 0.18166 0.00074 -0.01022SPELLI NG 0.42644 0.18185 0.00019 -0.03421FYREDC 0.42666 0.18204 0.00019 -0.03885HOSTILTY 0.42686 0.18221 0.00017 -0.08893ELEMINTR 0.42703 0.18236 0.00015 -0.04248BIRTHORD 0.42719 0.18249 0.00014 0.05835FRNDLANG 0.42733 0.18261 0.00011 0.00197PREGPROB 0.42746 0.18273 0.00012 -0.04758HANDWRIT 0.42761 0.18285 0.00012 0.00742FRDVISTS 0.42771 0.18293 0.00002 0.02142BOOKSRD 0.42781 0.18302 0.00009 0.01811BOOKSHM 0.01648FAGEBIR 0.11065FJOBMOB -0.00798GRDVSFRD 0.09270NOFETALD -0.04758SIZESIB -0.01238

TABLE 50 SMR WITH EQ VARIABLES PREDICTING AJA MEMORY


FATHAWAY 0.13634 0.01873 0.01873 -0.13684TEMPERMT 0.18895 0.03570 0.01698 0.13114PTEMPERM 0.24159 0.05837 0.02266 -0.10803ROOMMATE 0.25907 0.06712 0.00875 0.10874BOOKSHM 0.27237 0.07419 0.00707 0.07485FJOBMOB 0.28360 0.08043 0.00624 -0.06035SOCPAR 0.29469 0.08684 0.00641 -0.07633NOFETALD 0.30500 0.09303 0.00619 0.08337MATH 0.31237 0.09758 0.00455 0.07356MAGEBIR 0.31914 0.10185 0.00428 0.08978NOPREG 0.32410 0.10504 0.00319 0.03508SCHOLAR 0.32932 0.10845 0.00341 0.02867PIDGIN 0.33585 0.11280 0.00435 -0.01879GRADES 0.34147 0.11660 0.00381 0.05739SIZECITY 0.34528 0.11922 0.00261 0.05111SIZEHOME 0.34921 0.12195 0.00273 -0.04174PSCHOLAR 0.35202 0.12392 0.00197 -0.05301DEVPPROB 0.35457 0.12572 0.00180 0.04196HANDWRIT 0.35663 0.12718 0.00147 -0.04389AMTTV 0.35867 0.12865 0.00146 0.01579FAGEBIR 0.36058 0.13002 0.00137 0.06125HOSTILTY 0.36219 0.13118 0.00117 -0.07059ANXIETY 0.36495 0.13319 0.00200 -0.01228DEPRESS 0.36754 0.13508 0.00190 -0.05671SPELLING 0.36920 0.13631 0.00122 -0.03466MYREDC 0.37070 0.13742 0.00111 0.08336GRVSFRD 0.37169 0.13815 0.00074 0.01101HOMEWORK 0.37272 0.13392 0.00076 -0.04141NURSERY 0.37361 0.13958 0.00066 0.05449AGE 0.37449 0.14024 0.00066 -0.07936YRSEDC 0.38057 0.14483 0.00459 -0.11276FRNDLANG 0.38132 0.14540 0.00057 -0.01152BIRTHORD 0.38197 0.14590 0.00050 0.04018JOB 0.38238 0.14622 0.00031 -0.06398FYREDC 0.38274 0.14649 0.00027 0.05158SEX 0.38303 o•14671 0.00023 0.00536BOOKSRD 0.38329 0.14691 0.00020 0.00294MAGREAD 0.38386 0.14735 0.00043 0.04753FRDVISTS 0.38399 0.14745 0.00010 -0.02251ELEMINTR 0.38410 0.14753 0.00009 -0.02717READING 0.38417 0.14759 0.00005 -0.00215PREGPROB 0.38423 0.14763 0.00005 0.01698FAMINCOM 0.02554FNORC 0.03243SIZESIB 0.00195

TABLE 51 SMR WITH EQ VARIABLES PREDICTING AJA SPEARMAN'S 'G'


GRADES 0.24589 0.06046 0.06046 0.24589FATHAWAY 0.29761 0.08857 0.02811 -0.17073MATH 0.31811 0.10119 0.01262 0.12584BOOKSHM 0.33962 0.11534 0.01415 0.15797MAGREAD 0.35521 0.12617 0.01083 0.12738TEMPERMT 0.36473 0.13303 0.00685 0.12338PTEMPERM 0.37999 0.14439 0.01136 -0.03049PSCHOLAR 0.39865 0.15892 0.01453 0.13954SCHOLAR 0.40776 0.16627 0.00735 0.12218SIZEHOME 0.41446 0.17177 0.00551 -0.02148HANDWRIT 0.42060 0.17690 0.00513 -0.06021MYREDC 0.42645 0.18186 0.00495 0.15587NURSERY 0.42987 0.18478 0.00293 0.10746HOSTILTY 0.43263 0.18717 0.00238 -0.08340HOMEWORK 0.43495 0.18918 0.00202 0.02889AGE 0.43765 0.19154 0.00236 -0.02107YRSEDC 0.44256 0.19586 0.00432 -0.05546DEPRESS 0.44461 0.19768 0.00182 -0.02805SIZESIB 0.44644 0.19931 0.00163 -0.01977ROOMMATE 0.44966 0.20220 0.00289 0.02489NOFETALD 0.45187 0.20419 0.00199 0.03800SIZECITY 0.45379 0.20593 0.00174 0.07625MAGEBIR 0.45582 0.20778 0.00185 0.08022FYREDC 0.45765 0.20944 0.00167 0.10840PREGPROB 0.45957 0.21121 0.00176 -0.04569FRNDLANG 0.46167 0.21314 0.00194 0.06579FJOBMOB 0.46380 0.21511 0.00197 -0.06233ANXIETY 0.46543 0.21663 0.00152 -0.05155GRVSFRD 0.46681 0.21792 0.00129 0.14984FAMINCOM 0.46803 0.21905 0.00114 0.12631SPELLING 0.46936 0.22030 0.00125 -0.09400SEX 0.47049 0.22136 0.00106 0.05740FRDVISTS 0.47163 0.22243 0.00107 0.02348PIDGIN 0.47217 0.22294 0.00051 -0.04582BIRTHORD 0.47253 0.22329 0.00034 0.01098READING 0.47306 0.22378 0.00050 -0.00801DEVPPROB 0.47338 0.22409 0.00031 -0.05456FNORC 0.47366 0.22436 0.00027 0.11326AMTTV 0.47376 0.22444 0.00009 -0.02149ELEMINTR 0.47381 0.22449 0.00005 -0.04363JOB 0.47384 0.22452 0.00003 -0.05278BOOKSRD 0.09366FAGEBIR 0.09355NOPREG -0.00606SOCPAR 0.07956

TABLE 52 SMR WITH EQ FACTOR SCORES PREDICTING AJA VERBAL ABILITY


ACULTRTN 0.22104 0.04886 0.0488.6 -0.22104MAGBOOKR 0.27161 0.07377 0.02491 -0.19503HOB ILITY 0.31095 0.09669 0.02292 0.13847SOCPARFS 0.33833 0.11447 0.01778 0.19505FTLDNPRG 0.34609 0.11978 0.00531 0.06434CTYRURAL 0.34830 0.12131 0.00153 0.07140MOOD 0.35030 0.12271 0.00139 0.00356DEVPPREG 0.35196 0.12388 0.00117 -0.02886SES 0.35328 0.12480 0.00093 0.13282SELFRATG 0.35393 0.12527 0.00046 0.11280PARRATG 0.35514 0.12612 0.00085 0.05016SPELLMTH 0.35566 0.12649 0.00037 0.03093YREDCAGE 0.35605 0.12677 0.00028 0.04098FAMLYSIZ 0.35647 0.12707 0.00030 -0.05503FAMLYAGE 0.35683 0.12733 0.00026 0.03474READMATH 0.35691 0.12738 0.00006 -0.06259

TABLE 53 SMR WITH EQ FACTOR SCORES PREDICTING AJA SPATIAL ABILITY


SPELLMTH 0.15674 0.02457 0.02457 0.15674MOB IL1TY 0.19204 0.03688 0.01231 0.12948SOCPARFS 0.21997 0.04839 0.01151 0.10835SELFRATG 0.23136 0.05353 0.00514 O. 11350READMATH 0.24065 0.05791 0.00439 0.09151PARRATG 0.24685 0.06093 0.00302 -0.00229MAGBOOKR 0.25203 0.06352 0.00259 -0.06037FAMLYAGE 0.25756 0.06634 0.00282 0.04795CTYRURAL 0.26015 0.06768 0.00134 0.04375MOOD 0.26195 0.06862 0.00094 0.03063FTLDNPRG 0.26423 0.06982 0.00120 0.01290ACULTRTN 0.26598 0.07075 0.00093 -0.06844DEVPPREG 0.26647 0.07101 0.00026 -0.00263SES 0.26686 0.07122 0.00021 0.05516FAMLYSIZ 0.26710 0.07134 0.00012 -0.00831YREDCAGE 0.26715 0.07137 0.00003 0.05517

TABLE 54SMR WITH EQ FACTOR SCORES PREDICTING AJA PERCEPTUAL SPEED


SELFRATG 0.18263 0.03335 0.03335 0.18263MOBILITY 0.22048 0.04861 0.01526 0.12295DEVPPREG 0.24854 0.06177 0.01316 -0.11227READMATH 0.26299 0.06916 0.00739 0.09916FAMLYAGE 0.27846 0.07754 0.00838 0.10953SOCPARFS 0.29176 0.08513 0.00759 0.10125MOOD 0.29980 0.08938 0.00475 0.07801PARRATG 0.30493 0.09298 0.00310 0.04049CTYRURAL 0.31044 0.09637 0.00339 0.08088ACULTRTN 0.31345 0.09825 0.00188 0.02143YREDCAGE 0.31394 0.09856 0.00031 0.04074FTLDNPRG 0.31411 0.09867 0.00011 -0.04609FAMLYSIZ 0.31419 0.09871 0.00005 -0.00416MAGBOOKR -0.00971SES -0.01679SPELLMTH 0.04603

TABLE 55 SMR WITH EQ FACTOR SCORES PREDICTING AJA MEMORY


MOBI L1TY 0.11447 0.01310 0.01310 0.11447YREDCAGE 0.14671 0.02152 0.O084~; 0.10676SELFRATG 0.16891 0.02853 0.00701 0.08437PARRATG 0.19493 0.03800 0.00946 -0.07133FAMLYSIZ 0.20077 0.04031 0.00231 0.03225CTYRURAL 0.20719 0.04293 0.00262 -0.03231MOOD 0.21149 0.04473 0.00180 0.05165MAGBOOKR 0.21579 0.04657 0.00184 -0.03897ACULTRTN 0.21881 0.04788 0.00131 -0.02789DEVPPREG 0.22052 0.04863 0.00075 0.02901FAMLYAGE 0.22208 0.04932 0.00069 0.05757FTLDI~PRG 0.22326 0.04985 0.00053 0.02228READMATH 0.22390 0.05013 0.00029 0.03079SOCPARFS 0.22435 0.05033 0.00020 0.00881SES 0.22476 0.05052 0.00019 0.03778SPELU4TH 0.22492 0.05059 0.00007 0.04952

TABLE 56 SMR WITH EQ FACTOR SCORES PREDICTING AJA SPEARMAN'S 'G'


SELFRATG 0.21234 0.04509 0.04509 0.21234MOB I L1TY 0.26983 0.07281 0.02772 0.16583SOCPARFS 0.31532 0.09943 0.02662 0.20583MAGBOOKR 0.33108 0.10962 0.01019 -0.13849ACULTRTN 0.34190 0.11690 0.00728 -0.16304DEVPPREG 0.34592 0.11966 0.00276 -0.04678READMATH 0.35014 0.12260 0.00294 0.03217FTLDNPRG 0.35377 0.12515 0.00256 0.03154FAMLYAGE 0.35701 0.12745 0.00230 0.06998SPELLMTH 0.36033 0.12984 0.00238 0.10870CTYRURAL 0.36329 0.13198 0.00214 0.08354MOOD 0.36456 0.13290 0.00092 0.02294PARRATG 0.36566 0.13371 0.00081 0.08736SES 0.36672 0.13449 0.00078 0.09770FAMLYSIZ 0.36680 0.13454 0.00005 -0.03191YREDCAGE 0.05043

TABLE 57 SUMMARY OF SMR TABLES FOR AJAs

SMR's USING 16 FACTOR SCORES AS PREDICTORS

VERBSE SPATSE PERSPDSE------ ------ -------ACCULTRTN SPELLMTH SELFRATG*MAGBOOKR* MOB III TY* t-10B I LI TY*MOB III TY* SOCPARFS* 4.8% DEVPPREG 6.2*SOCPARFS* 11.4%

TOTAL VARIANCE 12.7% 7.1% 9.9%

MEMSE SPEAR'G'----- -------MOB III TY* 1.3% SELFRATG*

MOBI L1TY*SOCPARFS*MAGBOOKR* 11. 0%

TOTAL VARIANCE 5.3% 13.5%

SMR's USING ORGINIAL 45 EQ VARIABLES AS PREDICTORS

VERBSE

GRADES*FATHAWAY*MAG READBOOKSHM 11. 7%

TOTAL VARIANCE 21.5

MEMSE

FATHAWAY*TEMPERMT*PTEMPERM*

TOTAL VARIANCE

SPATSE

MATH*FATHAWAY*SEX 6.5

16.7%

SPEAR'G'

GRADES*FATHA\~AY*

5.8% MATH*BOOKSHM*TEMPERMT*PSCHOLAR

14.7%

PERPSDSE

TEMPERMT*t4ATH*PTEMPERM*SELFRATG*FATHAWAY* 10.2%

18.3%

15.9%22.5%

Variables appearing in more than one list.

BOOKSHM (2)PTEMPERM (2)

MOBILITY (5)SOCPARFS (3)MAGBOOKR (2)SELFRATG (2)

FATHA\"1AY (5)MATH (3)TEMPERt-1T (3)GRADES (2)

AJA regression tables

The variance accounted for by the 45 EQ variables is

respectively: verbal-22%, spatial-17%, perceptual speed-13%,

memory-15%, and Spearman's 'g'-23%. This is about the same

range of prediction as shown in the AEA group. Verbal

ability is most affected by ACCUlTRN, a variable related to

SESe Also important is the amount of outside reading, number

clubs involved with, and MOBiliTY. MOBILITY is important to

all of the abilities and has a negative effect. It appears

to be postively related due to its reflected signs from the

factor structure. By looking at all the SMR tables it is

clear that FATHAWAY is the variable responsible for this

wide ranging effect. The father being away from the home for

more than a year seems very important, but a problem exists

because this variable is badly skewed with only 8% of the

sample reporting absence of a year or more. Any conclusions

should be tempered with this in mind.

As with the AEAs spatial ability is most affected by

SPEllMTH, and again MOBiliTY and SOCPARFS show up.

Perceptual speed is related in similar ways for both AEAs

and AJAs with SELFRATG, MOBiliTY, and DEVPPREG being

important. MOBiliTY again appears v/ith memory and SCHOLAR,

MOBiliTY, SOCPARFS, and MAGBOOKR are important factors

across abilities, while FATHAWAY, MATH, TEMPERMT, GRADES,

BOOKSHM, and PTEMPERMT are important variables.

TABLE 58SMR WITH EQ VARIABLES PREDICTING KOREAN SPATIAL ABILITY


FJOB~10B 0.15226 0.02318 0.02318 0.15226FJOBSAT 0.18285 0.03343 0.01025 -0.10098HOMEWORK 0.20784 0.04320 0.00976 0.09519FAMINCOM 0.22874 0.05232 0.00913 0.06730PHEALTHF ·0.25520 0.06513 0.01280 -0.11199PDISCIPN 0.27781 0.07718 0.01205 0.07139NOFETALD 0.29763 0.08858 0.01141 -0.01523FRDVISTS 0.31534 0.09944 0.01085 -0.10629SIZEHOME 0.32323 0.10448 0.00504 -0.00809MAGEBIR 0.33053 0.10925 0.00477 -0.06304HANDUSE 0.33869 0.11471 0.00546 0.06501DISCIPLN 0.34547 0.11935 0.00464 -0.02818HEALTHFS 0.35947 0.12922 0.00987 0.06620TUTOR 0.36697 0.13467 0.00545 0.03800GRADES 0.37135 0.13790 0.00323 0.07948NURSERY 0.37513 0.14072 0.00282 -0.06457READING 0.37775 0.14270 0.00197 -0.05706PREPSCH 0.38009 0.14446 0.00177 0.02120PSOCABLE 0.38247 0.14628 0.00182 -0.00172OWNHOME 0.38473 0.14802 0.00173 0.02863BOOKSHM 0.38701 0.14978 0.00176 0.01449FATHNORC 0.38890 0.15124 0.00147 0.04387AGE 0.39106 0.15293 0.00169 -0.01979FAGEBIR 0.39366 0.15497 0.00204 -0.06473SEX 0.39596 0.15679 0.00182 0.02316DEVPVSOK 0.39825 0.15860 0.00181 0.08176PREGVSOK 0.40134 0.16107 0.00248 -0.02121EXPNORC 0.40329 0.16265 0.00157 0.10738BIRTHORD 0.40498 0.16401 0.00136 0.01911ROOMMATE 0.40663 0.16535 0.00134 -0.04435MATH 0.40814 0.16658 0.00123 0.06752FATHEDC 0.40955 0.16773 0.00116 0.07541YRSEDC 0.41092 0.16886 0.00113 0.02307BOOKSRD 0.41206 0.16979 0.00093 0.00066SIZESIB 0.41319 0.17073 0.00094 -0.02133NOPREG 0.41661 0.17356 0.00284 -0.04148ELEMINTR 0.41817 0.17486 0.00130 -0.02011SIZECITY 0.41947 0.17596 0.00110 0.03451MOTHEDC 0.41975 0.17620 0.00024 0.02274AMTTV 0.41983 0.17626 0.00006 -0.00199GRDVSFRD 0.01412SOCIABLE 0.03736SOCPAR 0.00789

TABLE 59 SMR WITH EQ VARIABLES PREDICTING KOREAN VERBAL ABILITY


GRADES 0.36459 0.13292 0.13292 0.36459SEX 0.38894 0.15128 0.01835 0.15220EXPNORC 0.42599 0.18147 0.03020 0.22609BOOKSHM 0.43886 0.19260 0.01113 0.15057SIZEHOME 0.44925 0.20183 0.00923 -0.05596OWNHOME 0.46137 0.21287 0.01104 0.16285GRDVSFRD 0.47119 0.22202 0.00915 0.22758NURSERY 0.48041 0.23079 0.00878 -0.04685AMTTV 0.48783 0.23798 0.00718 0.08075SIZECITY 0.49383 0.24386 0.00588 0.02718MOTHEDC 0.49878 0.24878 0.00492 0.13168FATHEDC 0.50664 0.25669 0.00790 0.09114SOCPAR 0.51254 0.26270 0.00601 0.07266FRDVISTS 0.51770 0.26801 0.00532 -0.15437BOOKSRD 0.52160 0.27206 0.00405 0.12976SOCIABLE 0.52536 0.27601 0.00394 -0.04211FJOBSAT 0.52853 0.27935 0.00334 0.12988MATH 0.53206 0.28309 0.00374 0.12140YRSEDC 0.53409 0.28525 0.00216 0.01961FAGEBIR 0.53667 0.28801 0.00277 0.04000PHEALTHF 0.53839 0.28987 0.00185 -0.00387PSOCABLE 0.54015 0.29176 0.00190 0.13295ELEMINTR 0.54207 0.29384 0.00208 0.05229DISCIPLN 0.54447 0.29644 0.00260 0.16697SIZESIB O. 5l~6 20 0.29833 0.00189 -0.09001HOMEWORK 0.54795 0.30024 0.00191 0.16208NOPREG 0.54933 0.30177 0.00152 -0.07681NOFETALD 0.55072 0.30330 0.00153 0.03612HANDUSE 0.55217 0.30489 0.00159 0.06644FATHNORC 0.55324 0.30607 0.00118 0.14021FJOBMOB 0.55549 0.30857 0.00250 0.04164PREGVSOK 0.55627 0.30944 0.00087 0.02372MAGEBIR 0.55664 0.30985 0.00041 -0.00870PREPSCH 0.55681 0.31004 0.00019 -0.01839ROOMMATE 0.55698 0.31023 0.00019 -0.11329AGE 0.55710 0.31037 0.00014 -0.02792PDISCIPN 0.55721 0.310l~9 0.00012 0.14354DEVPVSOK 0.55732 0.31060 0.00012 -0.00886BIRTHORD 0.55741 0.31070 0.00010 -0.10911READING 0.55745 0.31075 0.00005 -0.03632FAMINCOM 0.01398HEALTHFS 0.13276TUTOR -0.09592

TABLE 60 SMR WITH EQ VARIABLES PREDICTING KOREAN MEMORY


MOTHEDC 0.18625 0.03469 0.03469 -0.18625SIZEHOME 0.24061 0.05789 0.02320 -0.18083AMTTV 0.26991 0.07285 0.01496 0.13773NURSERY 0.28580 0.08168 0.00883 0.03597SIZESIB 0.29784 0.08871 0.00703 -0.05685EXPNORC 0.31022 0.09623 0.00752 -0.12544FATHEDC 0.32398 0.10496 0.00873 -0.03947PD ISCI PN 0.33323 0.11104 0.00608 0.03283PREPSCH 0.33917 0.11504 0.00400 0.03247SOC PAR 0.34541 0.11931 0.00427 -0.07118DISCIPLN 0.35042 0.12280 0.00349 -0.05743GRADES 0.35766 0.12792 0.00512 0.02766DEVPVSOK 0.36160 0.13076 0.00284 -0.05108SOCIABLE 0.36618 0.13409 0.00333 0.01903PREGVSOK 0.37015 0.13701 0.00292 0.01877FAGEBIR 0.37423 0.14005 O. 0030L~ 0.05630SIZECITY 0.37916 0.14376 0.00371 -0.02158MAGEBIR 0.38400 0.14745 0.00369 0.00222NOPREG 0.38792 0.15048 0.00303 0.01708FRDVISTS 0.39271 0.15422 0.00373 -0.08733AGE 0.39560 0.15650 0.00228 -0.01432YRSEDC 0.44354 0.19673 0.04023 0.09798TUTOR 0.44892 0.20153 0.00480 -0.04732OWNHOME 0.45350 0.20566 0.00414 -0.01430FJOBSAT 0.45621 0.20813 0.00247 -0.02243SEX 0.45826 0.21000 0.00187 0.10306PSOCABLE 0.46019 0.21177 0.00177 0.01052READING 0.46167 0.21314 0.00137 -0.02758ELElvtlNTR 0.46381 0.21512 0.00199 0.03254MATH 0.46558 0.21676 0.00164 -0.04301NOFETALD 0.46730 0.21837 0.00161 0.06259BOOKSRD 0.46898 0.21994 0.00157 0.05534HANDUSE 0.47034 0.22122 0.00128 0.03900BIRTHORD 0.47147 0.22229 0.00107 -0.02856ROOMMATE 0.47262 0.22337 0.00108 0.05358FAMINCOM 0.47404 0.22471 0.00134 -0.01303GRDVSFRD 0.47513 0.22575 0.00104 -0.00974BOOKSHM 0.47576 0.22634 0.00059 -0.03798FATHNORC 0.47627 0.22683 0.00049 -0.05556FJOBMOB 0.47673 0.22727 0.00044 -0.01674HEALTHFS -0.02822HOMEt~ORK -0.03636PHEALTHF 0.03891

TABLE 61SMR WITH EQ VARIABLES PREDICTING KOREAN ROTATIONAL SPEED


READING 0.154L~0 0.02384 0.02384 -0.15440HEALTHFS 0.20402 0.04162 0.01778 0.15389FAGEBIR 0.23886 0.05705 0.01543 -0.11355FAMINCOM 0.26202 0.06865 0.01160 0.09068SIZEHOME 0.29515 0.08711 0.01846 -0.09139FJOBSAT 0.31799 0.10112 0.01400 -0.07894GRDVSFRD 0.32831 0.10779 0.00667 0.07080AMTTV 0.33630 0.11310 0.00531 -0.05714AGE 0.34427 0.11853 0.00543 -0.04474NOPREG 0.35215 0.12401 0.00548 -0.00878SIZECITY 0.35719 0.12759 0.00358 -0.01346YRSEDC 0.36219 0.13118 0.00360 -0.00945TUTOR 0.36761 0.13514 0.00395 -0.06552ROOMMATE 0.37241 0.13869 0.00356 -0.05004NURSERY 0.37724 0.14231 0.00361 0.02284ELEMINTR 0.38167 0.14567 0.00337 0.00645DISCIPLN 0.38409 0.14752 0.00185 0.12478PDISCIPN 0.38793 0.15049 0.00297 -0.00240HANDUSE 0.39035 0.15237 0.00188 -0.05013MAGEBIR 0.39255 0.15409 0.00172 -0.01838NOFETALD 0.39467 0.15577 0.00167 0.08453FJOBMOB 0.39750 0.15800 0.00224 -0.05379SEX 0.39964 0.15971 0.00171 -0.02697BOOKSHM 0.40093 0.16075 0.00103 -0.04103FATHEDC 0.40338 0.16272 0.00197 0.07451BOOKSRD 0.40426 0.16343 0.00071 0.03294OEVPVSOK 0.40507 0.16408 0.00065 -0.03120SOCIABLE 0.40573 0.16462 0.00054 -0.06537BIRTHORD 0.40631 0.16509 0.00047 -0.01800FATHNORC 0.40681 0.16549 0.00040 -0.01770HOMEWORK 0.40722 0.16583 0.00033 0.03444MOTHEDC 0.40754 0.16609 0.00026 0.03768MATH 0.40788 0.16636 0.00027 0.11245OWNHOME 0.40803 0.16649 0.00012 0.02311SOCPAR 0.40816 0.16659 0.00010 0.03506PREGVSOK 0.40824 0.16666 0.00007 0.02187EXPNORC 0.02118FRDVISTS -0.06358GRADES 0.11267PHEALTHF 0.00763PREPSCH -0.01393PSOCABLE 0.05167SIZESIB -0.02455

TABLE 62 SMR WITH EQ VARIABLES PREDICTING KOREAN SPEARMAN'S 'G'


GRADES 0.28815 0.08303 0.08303 0.28815SIZEHOME 0.32757 0.10730 0.02427 -0.14088SEX 0.35154 0.12358 0.01628 0.12745HOMEWORK 0.37015 0.13701 0.01343 0.14339FAMINCOM 0.38806 0.15059 0.01358 0.07540FRDVISTS 0.40809 0.16654 0.01595 -0.20767READING 0.42221 0.17826 0.01172 -0.11651PDISCIPN 0.43196 0.18659 0.00832 0.13889PHEALTHF 0.44950 0.20205 0.01546 -0.05366SIZECITY 0.45829 0.21003 0.00798 0.02420FJOBSAT 0.46749 0.21855 0.00852 -0.03835EXPNORC 0.47512 0.22574 0.00719 0.14413YRSEDC 0.48381 0.23407 0.00833 0.06358AGE 0.50341 0.25342 0.01935 -0.04789OWNHOME 0.51130 0.26142 0.00801 0.10379HEALTHFS 0.51771 0.26802 0.00660 0.14295FJOBMOS 0.52227 0.27277 0.00475 0.10124SIZESIS 0.52627 0.27696 0.00419 -0.09176NOFETALD 0.53070 0.28165 0.00469 0.06077NOPREG 0.53860 0.29009 0.00844 -0.06323FAGEBIR 0.54286 0.29470 0.00462 -0.03745BIRTHORD 0.54724 0.29948 0.00477 -0.05997HANDUSE 0.55102 0.30362 0.00414 0.07890BOOKSRD 0.55351 0.30638 0.00276 0.10042DISCIPLN 0.55570 0.30880 0.00243 0.07534BOOKSHM 0.55839 0.31180 0.00300 0.06184MAGEBIR 0.56056 0.31423 0.00243 -0.05262ELEMINTR 0.56186 0.31568 0.00145 0.02838FATHNORC 0.56279 0.31673 0.00105 0.07120NURSERY 0.56365 0.31770 0.00096 -0.04583GRDVSFRD 0.56473 0.31892 0.00123 0.14398DEVPVSOK 0.56529 0.31955 0.00063 0.02033ROOMMATE 0.56566 0.31997 0.00041 -0.08160SOCIABLE 0.56603 0.32039 0.00042 -0.00530AMTTV 0.56633 0.32073 0.00034 0.08022PREPSCH 0.56661 0.32105 0.00033 0.01421PSOCABLE 0.56684 0.32131 0.00026 0.09399MATH 0.56692 0.32140 0.00009 0.12545FATHEDC 0.10522MOTHEDC 0.02351PREGVSOK 0.01228SOCPAR 0.02392TUTOR -0.06322

TABLE 63SMR WITH EQ FACTOR SCORES PREDICTING KOREAN SPATIAL ABILITY


WEALTH 0.09386 0.00881 0.00881 -0.09386DEVPPREG 0.12435 0.01546 0.00665 -0.08333READMATH 0.14023 0.01966 0.00420 0.08427PRVATSCH 0.14945 0.02234 0.00267 -0.03116NORCFS 0.15885 0.02523 0.00290 -0.04552NFTLDPRG 0.16546 0.02738 0.00214 -0.00727ROOMMATF 0.16979 0.02883 0.00145 0.04791EXPNORCF 0.17266 0.02981 0.00098 0.04675SELFRATG 0.17467 0.03051 0.00070 -0.01850FAMLYAGE 0.17623 0.03106 0.00055 -0.02938SCHOOLWK 0.17729 0.03143 0.00038 -0.05907YREDCAGE 0.17816 0.03174 0.00031 -0.00556FAMLYSIZ 0.17919 0.03211 0.00037 -0.04332SES 0.17943 0.03219 0.00008 0.03991PARRATG 0.17958 0.03225 0.00005 0.01295NURSERYF 0.00838

TABLE 64SMR WITH EQ FACTOR SCORES PREDICTING KOREAN VERBAL ABILITY


SCHOOLWK 0.26968 0.07272 0.07272 -0.26968NORCFS 0.32106 0.10308 0.03036 -0.19690PRVATSCH 0.35860 0.12859 0.02551 0.17664FAMLYSIZ 0.38781 0.15039 0.02180 -0.15576SES 0.40281 0.16226 0.01186 0.14398WEALTH 0.40916 0.16741 0.00516 -0.14387EXPNORCF 0.41563 0.17275 0.00533 0.07434YREDCAGE 0.41979 0.17623 0.00348 -0.00199ROOMMATF 0.42360 0.17943 0.00321 0.12246DEVPPREG 0.42762 0.18286 0.00342 0.03318READMATH 0.43159 0.18627 0.00342 0.12559NURSERYF 0.43247 0.18703 0.00076 0.11540PARRATG 0.43332 0.18776 0.00073 0.15174FAMLYAGE 0.43362 0.18803 0.00026 0.00612NFTLDPRG 0.00738SELFRATG 0.11641

TABLE 65 SMR WITH EQ FACTOR SCORES PREDICTING MEMORY - KOREANS


NFTLOPRG 0.13844 0.01917 0.01917 0.13844EXPNORCF 0.19346 0.03743 0.01826 -0.13128FAMLYSIZ 0.22133 0.04899 0.01156 -0.09146OEVPPREG 0.23761 0.05646 0.00747 0.05971PRVATSCH 0.25443 0.06474 0.00828 0.11706SCHOOLWK 0.26290 0.06912 0.00438 0.06440NURSERYF 0.27202 0.07400 0.00488 0.08792SES 0.27771 0.07712 0.00313 -0.08668YREDCAGE 0.28189 0.07946 0.00234 -0.04358READMATH 0.28294 0.08005 0.00059 0.00285PARRATG 0.28350 0.08037 0.00032 -0.00166ROOMMATF 0.28401 0.08066 0.00029 -0.03755SELFRATG 0.28449 0.08094 0.00028 -0.00216NORCFS 0.28479 0.08111 0.00017 0.01972WEALTH 0.28490 0.08117 0.00006 -0.06769FAMLYAGE 0.01984

TABLE 66SMR WITH EQ FACTOR SCORES PREDICTING KOREAN ROTATIONAL SPEED


READMATH 0.17067 0.02913 0.02913 0.17067SELFRATG 0.18699 0.03497 0.00584 0.09393FAMLYSIZ 0.19457 0.03786 0.00289 -0.05967NFTLDPRG 0.20200 0.04080 0.00295 0.05335FAMLYAGE 0.20899 0.04368 0.00287 -0.04501SCHOOLWK 0.21425 0.04590 0.00222 -0.08661NURSERYF 0.21968 0.04826 0.00236 -0.00269NORCFS 0.22432 0.05032 0.00206 0.02837DEVPPREG 0.22828 0.05211 0.00179 0.01944YREDCAGE 0.23183 0.05374 0.00163 0.02941EXPNORCF 0.23543 0.05543 0.00168 -0.01391SES 0.23822 0.05675 0.00132 0.05268PRVATSCH 0.24055 0.05791 0.00116 0.04510ROOMMATF 0.24285 0.05898 0.00106 0.04709PARRATG 0.24491 0.05998 0.00100 0.02407WEALTH 0.24520 0.06012 0.00014 -0.06796

PAGE III

TABLE 67SMR WITH EQ FACTOR SCORES PREDICTING KOREAN SPEARMAN'S 'G'


WEALTH 0.18703 0.• 03498 0.03498 -0.18703READMATH 0.23872 0.05699 0.02201 0.17691FAMLYSIZ 0.28032 0.07858 0.02159 -0.16572NORCFS 0.30845 0.09514 0.01656 -0.11399SCHOOLWK 0.32661 0.10667 0.01153 -0.17825PRVATSCH 0.34089 0.11621 0.00953 0.13135ROOMMATF 0.34613 0.11980 0.00360 0.09439YREDCAGE 0.35116 0.12331 0.00351 -0.01355NFTLDPRG 0.35371 0.12511 0.00179 0.07320SES 0.35597 0.12672 0.00161 0.08124DEVPPREG 0.35711 0.12753 0.00081 -0.00920NURSERYF 0.35755 0.12784 0.00032 0.10001FAMLYAGE 0.35798 0.12815 0.00030 -0.02307PARRATG 0.35833 0.12840 0.00025 0.09293EXPNORCF 0.35850 0.12852 0.00012 0.01085SELFRATG 0.07545

TABLE 68 SUMMARY OF SMR TABLES FOR KOREANS

SMR's USING 16 FACTOR SCORES AS PREDICTORSSPAT IAL VERBAL MEMORY

TOTAL VARIANCE 3.2%

SCHOOLltIK*NORCFS*PRVATSCHFAMLYSIZ*SES 16.2%

18.8%

NFTLDPRGEXPNORCFFAMLYSIZ* 4.9%

8.1%

ROTATSPD SPEAR'G'

READMATH*

TOTAL VARIANCE

2.9%

6.0%

WEALTHREADMATH*FAMLYSIZ*NORCFS*SCHOOLWK* 10.7%

12.9%

SMR's USING ORGINIAL ORGINIAL 43 VARIABLES AS PREDICTORSSPAT IAL VERBAL MEMORY

FJOBMOBFJOBSAT*HOMEWORK*FAMINCOM*PHEALTHF*PDISCIPN*NOFETALDFRDVISTS* 9.9%


ROTATSPD

GRADES*SEX*EXPNORCBOOKSHMSIZEHOME*OWNHOME 22.2%

31.1%

SPEAR'G'

MOTHEDCSIZEHOME*AMTTV 7.3%

22.7%

READING*HEALTHFSFAGEBIRFAMINCOM*SIZEHOME*FJOBSAT* 10.1%


GRADES*SIZEHOME*SEX*HOME~JORK*

FAMINCOM*FRDVISTS*READING*PDISCIPN*PHEALTHF* 20.2%

32.1%

* Variable appearsFAMLYSIZ (3)SCHOOL\"lK (2)NORCFS (2)READMATH (2)

more than once inSIZEHOME (4)FAM I NCOM (3)FJOBSAT (2)HOME~JORK (2)PDISCIPN (2)

1 ists.FRDVISTSGRADESSEXREADINGPHEALTHF

(2)(2)(2)(2)(2)

Korean regression tables

The variance accounted for by the 43 orginial EQ

variables is respectively: spatial-18%, verbal-31%,

memory-23%, rotational speed-17%, and Spearman's 'g'-32%.

Spatial ability is affected by many of the factors, but

strongly by none. Again the verbal factor is influenced by

SCHOOLWK, NORCFS, PRVATSCH, FAMLYSIZ, and SESe Memory

ability is related to number of fetal deaths and

pregnancies, EXPNORC, and FAMLYSIZ. READMATH is important to

rotational speed and WEALTH, READMATH, FAMLYSIZ, NORCFS, and

SCHOOLWK to Spearman's 'g'.

FAMLYSIZ, SCHOOLWK, READMATH, and NORCFS are important to

more than one ability, while FAMINCOM, SIZEHOME, FJOBSAT,

FRDVISTS, GRADES, SEX, READING, HOMEWORK, and PDISCIPN are

variables important to two or more abilities.

Spearman rank correaltions

The next two tables show how a rank ordered pattern of EQ

correlations with a specific abil ity relate to patterns from

combinations of other groups and other abilities.

The pairwise comparisons across abil ity are shown first

and the comparisons across ethnic groups next. The AEA and

AdA pairwise comparisons have 45 data points!n common

whereas any ethnic comparison with the Korean group has only

32 EQ variables in common. The within Korean comparisons

would obviously have 43 data points.

The significance levels for a N of 30 are rho=.31 for

p<.05 (one tailed test) and Rs=.43 for p<.Ol.

TABLE 69

RHO'S FOR EQ-ABILITY PATTERNS ACROSS ABILITY AND ETHNIC GROUP

AEAVERB/ AJAVERB .74 AEASPAT/AJASPAT .64AEAVERB/ KORVERB .51 AEASPAT/KORSPAT .35AJAVERB/KORVERB .46 AJASPAT/KORSPAT .03

AEAPS/AJAPS .47 AEAMEM/AJAMEM .01AEAPS/ KORSPD .48 AEAMEM/KORMEM .01AJAPS/ KORSPD .21 AJAMEM/KORMEM .06

AEASPG/ AJASPG .69AEAS PG/ KORSPG .47AJ AS PG/ KO RS PG .34

AEA AJA KOREAN

VERB/SPAT .76 VERB/SPAT .74 VERB/SPAT .48VERB/PS .76 VERB/ PS .41 VERB/RSP .57VERB/MEM .73 VERB/MEM .53 VERB/MEM -.12VERB/SPG .94 VERB/SPG .83 VERB/SPG .89SPAT/PS .81 SPAT/PS .73 SPAT/RSP .34SPAT/MEM .80 SPAT/MEM .77 SPAT/MEM -.27SPAT/SPG .89 SPAT/SPG .82 SPAT/SPG .71PS/MEM .79 PS/MEM .54 RSP/MEM -.14PS/SPG .86 PS/SPG .60 RSP/SPG .63MEM/SPG .81 MEM/SPG .57 MEM/SPG .02

As can be readily seen, the rho's are higher within

ethnic groups across abil ities, than within abilities across

ethnic groups. Certain environment-abil ity patterns, notably

verbal and Spearman's 'g', do show significant relations

across ethnic groups.

DISCUSSION

The discussion will stress the similarities rather than

the differences discerned in this study. This is done partly

from a philosophical bias and partly to simplfy the

approach. feel any lasting conclusions about the

influences of the environment on humans must come from a

cross-cultural approach. Also, there are fewer ways that a

multiple group of comparisons can be alike than different.

Strengths and limitations

A strength of this study is that is is based on the

responses of a large and heterogenous sample of individuals.

Although the subjects were solicited by advertisements and

thus self-selected, the range and diversity of the families

responding creates a firm foundation for generalizing to the

overall population. A second strength is the cross cultural

nature of the study. Generalizations about humans often are

built on shaky ground, but evidence from two cultures and

three ethnic stocks gives force to the interpretations.

My bias in viewing the data is this: the AEAs and AJAs

have been brought up in the American culture and although

the rich Japanese culture in Hawaii offers a different

tradition and roots for the AJAs than the AEA1s, their

general environment is much the same as AEAs. The native

Korean sample offers not only an ethnic difference but a

truly different cultural setting. Also it is a culture which

draws its experience from a philosophical tradition quite

different from the West. This cross cultural aspect will act

as a criterion for the way the data is summarized and

discussed.

A second emphasis will be the analysis of the relative

importance of each environmental factor to cognitive

abil ities. The amount of variance related to environment for

each ability Is important, but subject to certain

limitations, to be mentioned below. For this reason, the

emphasis is not on "how much", but on "how" and "in what

way".

There are two reasons for this. First, for almost every

variable the argument could be made that the variable does

not simply represent the independent contribution of

environment, but also represents an unknown amount of

variance resulting from an interaction and/or correlation of

heredity and environment, as well as purely genetic effects.

The data presented does not allow for separation of these

effects. A second limitation is the semanticist's

distinction between the object and its label. The total

environment affecting cognitive abil ities is the ideal, and

the variables used to describe the environment, the reality.

Communalities and eigenvalue structures for thethree ethnic groups

The communalities of the environmental variables differ

across ethnic groups but are generally in the same range.

The Spearman rank correlations of the rank ordered

communalities are .92, .75, and .70 for AEA versus AJA, AEA

versus Korean, and AJA versus Korean, respectively.

Using Kaiser's criterion, all three eigenvalue structures

gave a 16 factor solution. After examining alternate numbers

of factors for each group and for reasons of consistency, 16

factors were chosen to rotate in each case.

The three eigenvalue structures are similar and show good

condensation of information with the 16 factors accounting

for 64.2% of the variance of 45 variables for AEAs, 67.7% of

the variance of 45 variables for AJAs and 67.5% of the

variance of 43 variables for the Koreans. In each case, the

number of factors were about one-third the number of the

original variables and accounted for approximately

two-thirds of the total variance.

Congruency of factors across groups

Each factor which appeared is presented below. They are

discussed in order of their strength of similarity across

groups. Similarities are indicated by the congruency

coefficients presented earlier. Below is a summary table of

the congruency coefficients between factors for each paired

comparison of the three ethnic groups. They are presented in

ranked order. A summary table also is shown of how the

factors related to abil ities across groups.

TABLE 70

Congruency coefficients of factors across groups

AEA vs AJA AEA vs Korean AJA vs Korean

FAMLYSIZ .92 FAMLYSIZ .90 FAMLYAGE .92MOOD -.92 FAMLYAGE -.84 YREDCAGE .87READMATH -.89 READMATH -.84 FAMLYSIZ .86SPELLMTH -.87 NORCFS -.82 PARRATG .84MAGBOOKR -.87 SES .81 ACCULTRN .80FAMLYAGE -.85 YREDCAGE -.80 READMATH .78NORCFS .85 FTLDNPRG .72 DEVPPREG -.72FTLDNPRG .83 DEVPPREG -.69 SES .70YREDCAGE -.83 ROOMMATF .62 NORCFS -.70SES .78 SELFRATG -.67MOBILITY -.71ACCULTRN -.67DEVPPREG .62

Simple correlations of factors with cognitive abilities

AEA AJA KOREAN

VER SPT PS MEM SPG VER SPT PS MEM SPG VER SPT RTS MEM SPGSES 25 16 07 06 27 13 06 -02 04 10 14 04 OS -09 08DEVPPREG -08 -10 -16 -04 -13 -03 -00 -11 03 -05 03 -08 02 06 -01PARRATG -16 -16 -16 -12 -24 as -00 04 -07 09 15 01 02 -00 09READMATH 11 -06 -07 01 01 -06 09 10 03 03 13 08 17 00 17SELFRATG -12 -09 -17 -os -17 11 11 18 08 21 11 -01 09 -00 08FTLDNPRG 00 -04 -07 -02 -02 06 01 -05 02 03 00 -01 05 14 07YREDCAGE 11 08 07 08 12 04 06 04 11 05 -00 -01 03 -04 -01FAMLYAGE -03 -08 01 -03 -06 03 05 11 06 07 01 -03 -05 02 -02FAMLYSIZ -03 -01 -05 02 -03 -06 -01 -00' 03 -03 -16 -04 -06 -09 -17MAGBOOKR 27 09 13 08 23 -20 -06 -01 '-04 -14SPELLMTH -03 -17 -08 -04 -12 03 16 05 05 11MOOD -03 -06 -06 -07 -07 00 03 08 os 02MOBILITY -01 -06 04 -03 -02 14 13 12 11 17SCHOOLWK 31 12 24 08 32 -27 -06 -09 06 -18ROOMMATF 07 07 08 03 12 12 05 05 -04 09NORCFS 01 04 -01 02 03 -20 -05 03 02 -11ACCULTRN -22 -07 02 -03 -16SOCPARFS 20 11 10 01 21CTYRURAL 07 04 08 -03 08NURSERY 12 01 -00 09 10WEALTH -14 -09 -07 -07 -19PRVATSCH 18 -03 05 12 13EXPNORC 07 05 -01 -13 01

Congruency coefficients presented in the following

sections are always given in the order of AEA versus AJA,

AEA versus Korean, and AJA versus Korean.

Family size and family age

The first two factors, those with the highest congruency

coefficients, both deal with aspects of the family. Family

structure is a basic unit in the environment of the child.

It is pervasive around the world, although it may be

contrasted with orphanages or such chosen alternatives, as

the Kibbutzim.

Though family structure has many different aspects across

cultures, the concepts of FAMLYSIZ and FAMLYAGE would apply

to all cultures. FAMLYSIZ has the highest similarity across

groups with coefficients of .92, .90, and .86. The major

variable loadings are SIZESIS, NOPREG, and BIRTHORD. Family

size has attracted attention in the past stemming from the

concern that low intell igence families had more offspring

(Cattel, 1936). Fear was expressed that the intelligence of

the race was dropping. Other studies (Higgins, Reed, and

Reed, 1962) have shown problems with this view, mainly

because of the non-reproduction of extremely low

intell igence individuals. These data shows a consistently

negative, but low relationship between family size and

cognitive abilities for the American sample and a slightly

higher negative relationship for the Koreans.

The relationship between family size and SES is

negligible for the American sample and has a correlation of

-.11 for the Korean sample. There has been a drastic

reduction in family size in this century and the possibility

exists that relationships that were strong earlier in the

century have been reduced.

Family age also has high similarity coefficients: -.85,

-.8~, and .92. The congruency coefficients sometimes show

negative signs because the signs of the factor loadings vary

from structure to structure. Only the magnitude is of

importance here. The main loadings are mother's age at

birth, father's age at birth, and birth order. These

loadings reflect how old the parents were when the child was

born. The factor has low positive correlations for AEAs and

AJAs and correlations of mixed direction for Koreans.

Greater maturity of older parents may be operating here,

though it is a modest effect.

Years of education and age

YREDCAGE is next, with congruency coefficients of -.83,

-.80, and .87. The major loadings are years of education,

age of subject, and whether the subject has a job. (The JOB

variable did not exist for the Koreans.> YREDCAGE's

relationship with cognitive abilities are all positive

though small for AEA'S and AJAs, with again mixed results

for Koreans.

This factor reflects measuring time by two variables,

years of age, and years of education. It does point to a

sal lent characteristic of any personal environment--that of

age or years of experience. Corrections are made within the

data for age and sex relationships so subjects could be

considered as a single group. Although the relation of age

to cognitive abilities is artifically reduced (through age

correcting scores) in this study, age represents an

important environmental dimension.

READMATH and SPELLMTH

READMATH and SPELLMTH are the two factors resulting from

the subject's rank ordering of four abil ities: reading,

writing, spelling, and mathematics. There was no spelling

rating for Koreans again because of the nature of their

language. Consequently the READMATH factor appeared across

all three groups while SPELLMTH appeared only in the AEA and

AJA groups. The coefficients for READMATH were -.89, -.84,

and .78. The AEA versus AJA coefficient for SPELLMTH was

-.87. The factors represent the tendency of math skill to be

ranked oppositely from either reading or spelling.

The two factors have some of the stronger relationships

to the cognitive abilities. A person who reported being more

proficient at math than spell ing tended to do better at

every abil ity for AEAs and AJAs, with math ability being

especially important to spatial abil ity and Spearman's 'g'.

A person who reported being better at reading than math

tended to be more adept at verbal ability among AEAs and

AJAs. Koreans who reported being better at math than reading

tended to be more skillful on all the cognitive abilities.

Although it is difficult to general ize about these two

dimensions, as a consequence of the artifical nature of

factoring rank ordered variables, they do show that persons

recognize their particular cognitive strengths and

presumably follow paths that use their skills to best

advantage.

Socio-economic status

Socio-economic status probably' is the most widely

discussed dimension relating to cognition. In each ethnic EQ

structure there are at least two factors relating to this

concept. This is in part caused by the large number of SES

type variables included, but it does show how dimensions

within this concept change from group to group.

The picture is complex. The SES and NORCFS factors appear

in both AEA and Korean groups, while SES and ACCULTRN appear

in the AJA group. The variables of parents' education

predominate in the AEA and Korean groups, forming the SES

factor, leaving the NORC-related variables to form NORCFS.

In the AJA group, the variable loadings that form SES and

ACCULTRN are more mixed. The acculturation label is crude at

best, and it is possible the factors should be more

cautiously named SESI and SES2. There is a further

complication. Dr. Park, in gathering the data in Korea added

variables he thought to be important (i.e. TUTOR, PREPSCH,

FJOBSAT, and OWNHOME). Traditionally all of these could be

considered as part of the concept of SESe These variables

form the added factors of WEALTH and PRVATSCH for Koreans.

It turns out, however, that WEALTH and PRVATSCH are not

very similar to the aforementioned SES dimensions from the

AEA and AJA groups. These four factors (SES, NORCFS, WEALTH,

and PRVATSCH) form second order factor numbers two and six

in the Korean structure. The socio-economic concept is

broken into second order factors of wealth, education and

reading for Koreans. Although this could possibly be true of

the AEA and AJA samples also, it cannot be shown because the

same variables which measured wealth were not included in

the BBL sample.

The similarities with regard to the three factors of SES,

NORCFS, and ACCULTRN can best be shown in Table 71 below.

NORCFS, AND ACCULTRNAJA vs. KOREAN

.70

CONGRUENCE FOR SES,AEA vs. KOREAN

.81-.82

-.80.39

to understanding the interrelationships

-.67.85key

COEFFICIENTS OFAEA vs. AJA

.78

TABLE 71

SESNORCFSSES - ACCNORC - ACC

A possible

here is the factor ACCULTRN. It appears only in the AJA

sample and has a high congruence with AEAs' NORCFS and

Koreans' SESe ACCULTRN's loadings are: BOOKSHM (-.55),

FYREDC (-.42) PIDGIN (.41), MYREDC (-.38), and TEMPERMT

(.30). Separating the socio-economic dimension temporarily,

ACCULTRN would seem to be more on the social than the

economic side. Family income has a moderate loading '(.57)

for SES in the AJA sample, but a low one (-.25) for

ACCULTRN. ACCULTRN seems to fit more closely the classical

idea of culture.

In the AEA and Korean structures there seems to be more

of an education versus job break, whereas in the AJA group

there is a job versus culture break.

SES is highly similar ~cross all groups. ACCULTRN is

similar to ~NORCFS for the AEAs and to SES for the Koreans.

NORCFS Is highly similar between AEA'S and Koreans.

Development and pregnancy problems & fetal deathsand number of pregnancies

The next two factors relate to pregnancies and

developmental problems. Problems during pregnancy and in

development show a positive relationship forming DEVPPREG.

Number of fetal deaths and number of pregnancies form

FTLDNPRG. The number of fetal deaths is of course, a subset

of the number of pregnancies, which helps create the

relationship of the factor.

The congruency coefficients for DEVPPREG are .62, -.69,

and -.72. Coefficients for FTLDNPRG are .83, .72, and .49.

DEVPPREG had a negative relationship with 11 of 15 abilities

across groups, with the positive relationships being small

and mostly in the Korean sample. Pregnancy and developmental

problems' negative influence is most pronounced with regard

to perceptual speed in the AEA and AJA groups. AEAs have

higher negative correlations as a group with perceptual

speed, Spearman's 'g', and spatial abil ity being most

affected. Correlations for FTLDNPRG with abilities is mixed.

Its highest correlation is with memory Cr=.14) for the

Korean sample. It seems that pre-natal trauma and later

developmental problems adversely affect cognitive abilities,

especially perceptual speed.

Parental and self ratings

The PARRATG and SELFRATG factors represent the eleven

adjective check list questions described earl ier in the

method. In the AEA and AJA groups, SELFRATG's major loading

is the SCHOLAR variable. It reflects loadings from the

adjective check list indicating a combination of motivation

and interest in school (i.e. studious, hard working, and

dependable). The PARRATG for AEA'S and AJAs reflects a more

even mixture of PSCHOLAR and PTEMPRMT, which then becomes a

measure of how positively or negatively the parent rated

his/her child on the eleven adjectives.

Though SELFRATG and PARRATG also apply to the Korean

group the loadings forming them are different. Factoring the

eleven original adjectives produced three factors called

DISCIPLN, SOCIABLE, and HEALTH with corresponding factors

for the parents' ratings. These names are conceptual

interpretations given the specific factor loadings and

certainly are open to reinterpretation. These data show that

Koreans rate themselves differently than AEAs and AJAs. In

the American culture, the adjectives happy, relaxed, and

easy contrast wnth studious, dependable, and hard-working,

forming two factors, TEMPERMNT and SCHOLAR. In the Korean

sample popular, bright, and easy load together forming one

factor (i.e. a discipl ine obedience dimension), while

well-organized, even-tempered, studious, dependable,

hard-working, and bright form the second (SOCIABLE). The

third factor consists of a major health loading with lower

loadings of relaxed, even-tempered, and happy.

The two factors, SELFRATG and PARRATG, have low

congruency coefficients between the AEA and AJA groups. This

is due to the reversed loadings for SCHOLAR and PSCHOLAR in

the AEA group. I decided not to arbitarily change signs in

the analyses so that a reader might trace the flow of

relations through the analyses, and in order not to

introduce error by changing one sign and not another. If

just the signs for SCHOLAR and PSCHOLAR were changed,

however, and the congruency coefficients recomputed, they

jump to -.85 and -.76 for PARRATG and SELFRATG between AEA

and AJA groups.

The SELFRATG factor shows positive correlations with

abil ity level across all groups. It relates most strongly to

Spearman's 'g' and perceptual speed in the AEA and AJA

groups. PARRATG has generally positive relations with

abil ities, having the most influence on AEAs as a group and

also to Koreans' verbal ability.

Remaining factors common to AEA and AJA groups

MOOD, SPELLMTH, MAGBOOKR, and MOBILITY are all factors

that appeared in the AEA and AJA group, but not in the

Korean group. This is mainly because the variables making up

these factors are missing for the Korean subjects.

The MOOD factor, composed of the Multiple Affect

Adjective List ratings of anxiety, depression, and

hostility, had the highest congruence (-.92). It represents

a crude pathology, or possibly, self-esteem dimension that

was significant for four out of ten negative relationships.

It has small effect but is consistently negative.

SPELLMTH and MAGBOOKR have the same congruency

coefficient (-.87>. SPELLMTH is one of two factors which

come from the subject's rank ordering of four abil ities:

reading, writing, spelling and mathematics. SPELLMTH

especially influences spatial ability and Spearman's 'g' in

both groups. Rating oneself higher on spelling than math was

negatively related to every ability in both groups. The

oppressed minority of poor spellers may take heart.

The amount of reading, as represented by the MAGBOOKR

factor, has a positive relationship to every abil ity. It has

the second highest relationship to verbal ability for AEAs

and AJAs. It is comforting to know that encouraging someone

to read is 1ikely to raise their verbal abil l tv ,

MOBILITY is the last factor common to AEAs and AJAs, and

is the least similar (-.71). It has a generally negative

effect, but is strongest for AJAs. It has a significant

negative relationship to every AJA ability. The father being

away for more than one year seems to be the main reason for

this and AJAs are most affected. This is a very indirect

means of measuring an aspect of home environment, but it has

a strong relationship to abil ity level.

Remaining factors common to the AEA and Korean groups.

Three factors were common to the AEA and Korean groups:

SCHOOLWK, ROOMMATF, and NORCFS. NORCFS already has been

discussed. SCHOOLWK has a low congruency coefficient of

-.40. The factor has a substantial sex loading for AEAs but

not for Koreans. SCHOOLWK has the largest relationship with

verbal ability of all factors for both groups. SCHOOLWK also

has the highest relationshIp to Spearman's 'g' for AEAs and

is second for Koreans. It Is clear that doing well in school

is positIvelY related to cognItive abilities. However,

whether school performance is the cause or the result of

intelligence remains a question.

ROOMMATF represents a combination of how many persons the

subject shares a room with and the size or ownership of the

house for AEA'S and Koreans. The congruency coefficient is

.62. Its relationshIp to all abil ities is negative (Le.

subjects who share rooms and 1 ive in smaller houses do

worse) except for the Korean memory factor. Five of the ten

relations are signIficantlY negative, but all have low

correlatIons.

Factors unIque to the AJA group.

ACCULTRN, SOCPARFS, and CTYRURAl are unique to the AJA

sample, although they have varying degrees of congruence

wIth factors from the other two groups. ACCULTRN has been

discussed previously. SOCPARFS, standing for social

participation, has moderate positive loadings on social

participation (.43), grades (.33), and amount of television

watched (-.32). SOCPARFS indicates an amount of civic

actIvity or sociabilIty. It has congruency coefficients of

.50, .46, and .40 with SCHOOLWK, SES, and MAGBOOKR from the

AEA structure and .54, .44, -.40, and .37 with SES, PARRATG,

SCHOOLWK, and NURSERYF from the Korean structure. SOCPARFS

is clearly a different factor, unique to the AJA culture. It

is positively related to every ability. Spearman's 'g' and

verbal are most affected and it is significant for every

abil ity but memory.

CTYRURAL has moderate loadings on size of house (.37),

number of friends visiting (.36), and size of the city in

which the subj ect was bo rn in ( .31) • CTYRURAL is

insignificantly but positively related to every ability but

memory. Its largest congruency coefficient is with ROOMMATF

(.56) for AEAs and with NURSERYF (.57) from the Korean

structure.

Factors unique to the Korean group

EXPNORC, NURSERYF, PRVATSCH, and WEALTH are unique to the

Korean group. NURSERYF has a major loading on nursery school

(.60) and moderate loadings for own grades versus those of

friends (.39), and sex (,34). It has low congruencies of

.42, .41, and .37 with ROOMMATF, SCHOOLWK, and SES from the

AEA structure, and ·coefficients of .57, .44, .37, and .35

wi th CTYRURAL, SELFRATG, SOCPARFS, and ACCULTRN from the AJA

structure. NURSERYF is positively significant with verbal

abil l t v ,

PRVATSCH's major loadings are whether the subject has had

a private tutor (-.60), attended preparatory school (-.52),

and grades (-.31). All congruency coefficients are below .40

fO'r any factors from AEA and AJA groups. PRVATSCH's

relationships are significantly negative for verbal, memory,

and Spearman's 'g'. Special school lrig l s negative

relationship to ability could be an indicator of one of the

following. It could be that it was of no help, and,

possibly, hindered demonstration of abil ities. Or, it is

possible that chlldern were subject to special education

because they had a lower learning capacity, and while the

special schooling may have raised their ability level, they

remain below the average.

WEALTH has its highest loading on family income (.52),

followed by friends visits (.41) and parents' health rating

of the child (.34). Its highest congruency coefficients with

the AEA structure are .51 for ROOMMATF and .38 for SESe

Surprisingly it is negatively significant with verbal

ability and Spearman's 'g'. This seems counter intuitive and

no explanations are offered.

The last unique Korean factor is EXPNORC. The major

loading is the NORC rating of the offspring's expected job

(,90), It also has low loadings on sex (-.31) and amount of

television watched (-.31). EXPNORC has low congruencies with

factors from the other groups. It has mixed relationships to

abil ity but is significantly negatively related to memory

abi 1 i tv ,

Second order factors

The second order factor eigenvalue structures show a less

condensced array of information when compared with the first

order eigenvalue structures. The second order factors do,

however, relate to broad areas within the environment.

For the AEA group there clearly were six factors. The

factors are second order abstractions that are numbered

rather than named. Factor one had four loadings: SES(.92)

MAGBOOKR (.40), NORCFS (.38), and ROOMMATF (.33). It shows

how other factors variously relate to the SES dimension.

Interestingly, factor two centers on MOBILITY. The loadings

are: MOBiLITY (-.87), FAMLYAGE (.45), and SES (-.25). This

factor is puzzling and could be an important area of the

environment. MOBILITY also shows up in the AJA second order

structure, but Is combined differently. Factor three was a

combination of the two first order factors dealing with the

rank ordering of abil ities: READMATH (.78) and SPELLMTH

(.39). Factor four shows that later borns have a increased

chance of pregnancy and developmental problems. The loadings

are: FAMLYSIZ (.58), DEVPPREG (.56), and FTLDNPRG (.38).

Factor five is the clustering of the adjective check list

questions: PARRATG (.64), SELFRATG (.58), MOOD (.36), and

SCHOOLWK (-.34). Factor six shows the influence of age:

YREDCAGE (.40), SCHOOLWK (.30), SELFRATG (-.28), READMATH

(.25), and NORCFS (-.25). Some of these six factors are

repeated In the AJA group.

Six second order factors were also rotated In the AJA

group. Factor one again showed the adjective check 1 ist

relationship: SELFRATG (.70), PARRATG (.60), and SOCPARFS

(.39). Factor two centers on YREDCAGE (.63) along with

CTYRURAL (.31) and SES (.29). Factor three shows the

general ized socio-economic dimension with ACCULTRN (.71),

SES (-.41), SOCPARFS (-.34), and MOOD (.26) being the main

loadings. READMATH (-.81) is the core of factor four with a

small loading for MAGBOOKR (-.28). It represents a

generalized reading factor. Factors five and six both have

the first order MOBILITY factor in them. Factor six is like

factor two from the AEA structure except that the size of

the loadings are reversed: FAMLYAGE (-.65) and MOBILITY

(-.25). MOBILITY is also shown in factor five with loadings

of FAMLYSIZ (.50), MOBILITY (-.41) and FTLDNPRG (.38).

MOBILITY seems to be important concept for both cultures,

but interrelates to the other first order factors somewhat

differently across groups.

The Korean second order structure shows somewhat

different factors, probably because of the differences in

the original variables. Factor one was again the adjective

check list dimension of positive or negative parental and

self ratings (PARRATG, .78; SCHOOLWK, -.38; and SELFRATG,

.33). Factor two centers on the WEALTH (-.33) and PRVATSCH

(.27) dimensions. Factor three again represents the age

dimension: FAMLYAGE (.86) and YREDCAGE (.24). Factor four,

with loadings of ROOMATF (-.57), FAMLYSIZ (.38), and

DEVPPREG (.29), is somewhat 1 ike the family size dimensions

of the AEA and AJA structure. NURSERYF (.77) is the central

loading for factor five with moderate loadings for EXPNORC

(-.31) and SCHOOLWK (-.26). Again the socio-economic

dimension is shown by loadings on SES (-.79), SElFRATG

(-.31), and NORCFS (.25).

Roughly categorizing the second order factors from each

group, socio-economic status, m?bility, self-perceived

strength of the offspring, family size, age, parental and

self ratings are areas of influence for AEAs. For AJAs

parental and self ratings, age, socio-economic status,

reading, family size, and family age are important. For

Koreans, parental and self ratings, wealth, family age,

family size, nursery school, and socio-economic status show

up.

Clearly, socio-economic status, parental and self

ratings, family size, and family age are all important

dimensions within the cluster of environmental variables

chosen for examination in this study.

Multiple regression analyses

The multiple regression analyses show the cumulative

relationships between the environmental variables and

cognitive abilities. A great deal of interest has centered

on how much total variance in cognitive ability can be

accounted for by the environment. The totals, summarized

below describe, at best, the influence of environment, a

gene-environment interaction, and a gene-environment

correlation.

The total variances are presented in Table 72, so

comparisons can be made as to which abilities are most

related to environment.

TABLE 72 TOTAL COGNITIVE VARIANCES ACCOUNTED FOR BY THE16 EQ FACTORS AND 45 ORIGINAL EQ VARIABLES

Verb Spat AttSp Mem ' s '

16 factors 17 9 13 4 21AEA

45 vari ab 1es 23 14 18 7 26

16 factors 13 7 10 5 14AJA

45 variables 22 17 18 15 23

16 factors 19 3 6 8 13Korean

43 variables 31 18 17 23 32

Considering the original EQ variables, the range of

variance predicted for all abilities is 7 to 26% for the

AEAs, 15 to 23% for the AJAs, and 17 to 32% for the Koreans.

The ranges across ethnic group for each ability are: 21 to

31% for verbal, 14 to 18% for spatial, 17 to 18% for

attentional speed, 7 to 23% for memory, and 23 to 32% for

Spearman's 'g'.

Spearman's 'g' and the verbal factor are related most

strongly to environment, followed by attentional speed,

spatial abil ity, and memory. The range of values for each

ability shows close agreement across groups except for

memory. This instabil ity probably results from the lower

reliabilities of the tests composing the memory factor. The

relationships average 27% for Spearman's 'g', 25% for

verbal, 18% for attentional speed, 16% for spatial, and 15%

for memory. Averaging across the three groups, the range for

all cognitive abilities was 15 to 27%, giving a

conservative, but substantial, relation of cognitive

measures to environmental variables.

Verbal abil ity

Of the four cognitive abilities, verbal ability relates

most highly to the environment. The major factors relating

to verbal ability are SCHOOLWK, MAGBOOKR, and SES for AEAs;

ACCULTRN, MAGBOOKR, MOBILITY, and SOCPARFS for AJAs; and

SCHOOLWK, NORCFS, PRVASTSCH, FAMLYSIZ, and SES for Koreans.

Clearly, proficiency in school is positively related to

verbal ability. This is hardly surprising since the main

purpose of schooling is to teach verbal skills. The AEA and

Korean groups show SCHOOLWK to be the most important factor,

while for AJAs ACCULTRN is most important. ACCULTRN has

congruency coefficients of .50 and .40 with the SCHOOLWK

factor from the AEA and Korean structures respectively.

A second important dimension related to verbal skills is

the amount of reading a person enjoys. MAGBOOKR relates

strongly for the AEA and AJA groups while the factor is

missing for the Korean group. The only other factor showing

crossover effect for all groups is SESe I t is strongly

related in all groups, but appears lower in the AJA

regression list because of its relationship to ACCULTRN.

Congruency coefficients between SES and ACCULTRN for the AEA

and Korean groups are -.67 and -.80. respectively.

Within the AJA group, MOBILITY exhibits negative and

SOCPARFS positive influence. As mentioned earlier,

MOBILITY's influence is linked with the negative

relationship of the father being away from the home for more

than one year. MOBILITY relates negatively to all cognitive

abilities in the AJA group. SOCPARFS presents a positive

relationship, showing the positive influence of parental

community activities on verbal ability.

For the Korean group, NORCFS relates positively to verbal

ability while PRVATSCH and FAMLYSIZ relate negatively.

Verbal ability is positively related to performance in

school, amount of reading, and SESe These effects are shown

in all three ethnic groups, indicating they are important

influences on verbal ability across ethnic and cultural

groups.

Spat i a1 ab i 1 i t y

Spatial ability does shows' fewer cross group

relationships than does verbal ability. SPELLMTH, PARRATG,

and SES are important for AEAs; SPELLMTH, MOBILITY, and

SOCPARFS are important for AJAs; while no factor in the

Korean group rises above criterion. The top three Korean

factors relating to spatial ability were WEALTH, DEVPPREG,

and READMATH, accounting for two percent of the variance.

Spatial ability, as shown in previous studies

(Vandenberg, 1971), relates less to environmental measures

than does verbal ability (i.e. averaging 25% vs. 16% of the

variance). This may be a consequence of the selection of EQ

variables. Verbal ability has been more extensively studied

and emphasized In the school system. Because of the wide

research on verbal abll ity, more EQ variables may have been

chosen that relate to it. Through the hemisphere

specialization literature (Gazzaniga and Sperry, 1967),

spatial ability has received attention as an important

complementary ability to verbal skills.

SPELLMTH, a self report from the subject, is the factor

most strongly related to spatial abil ity for both AEAs and

AJAs. READMATH from the Korean sample is the closest related

factor to SPELLMTH (AEA congruency coefficient of -.52 and

an AJA coefficient of .37). It also shows influence on

spatial ability. The positive relations between the rank

ordering of math over other skills and spatial abil ity

indicates a strong spatial component to mathematics.

Socio-economic status also shows positive influence

across all three ethnic groups for spatial abil ity. This

SES-spatial relationship could be related to better health

and nutrition in higher SES famil ies or could reflect gene

effects.

Perceptual and rotational speed

These two factors were named differently because of their

different loadings. Perceptual speed is defined by loadings

of number comparisons (.84), subtraction and multiplication

(.81), and pedigrees (.41) for AEAs and AJAs. For Koreans,

the factor was renamed rotational speed and its main

loadings are subtraction and multipl ication (.76), card

rotations (.74),. and mental rotations (.58).

The only factor to cross over for the AEA and AJA groups

was DEVPPREG. If pregnancy and developmental problems were

reported, the subjects were do more likely to more poorly on

perceptual speed. For AEAs, both SCHOOLWK and PARRATG were

both positively significant with perceptual speed. SELFRATG,

with its high loading on the SCHOLAR variable, also is

positively significant and MOBILITY negatively significant

for AJAs.

In the Korean sample, the only factor meeting criterion

was READMATH. Subjects reporting being better at math than

reading were generally faster at rotational speed.

Perceptual speed is less closely related to environment

than is verbal skill or Spearman's 'gl, but is on a par with

spatial ability. Again this maya result of the cluster of

environmental variables chosen for this study. Nutritional

effects are an obvious environmental dimension not measured

in this study, which could affect attentional speed.

Memory

The memory ability presents interpretive problems. The

reliabilities for the American sample are visual

memory-immediate (VMI) equal to .37 and visual

memory-delayed (VMD) equal to .49, while VMI equals .75 and

VMD equals .76 for the Korean sample. The factor laodings

also differ somewhat with VMI (.85) and VMD (.85)

representing the memory factor for AEAs and AJAs, while VMD

(.83), VMI (.69), and PMS (.57) represent it for Koreans.

There are no consistent effects across groups, possibly

because of the Instability of loadings involved.

In the AEA group, memory is positively related to PARRATG

and for the AJAs negatively related to MOBILITY. The amount

of memory's variance accounted for by environmental

variables is small in the AEA and AJA samples, but more than

rotational speed and spatial abil ity in the Korean group.

For the Koreans, the memory factor is positively related

to FTLDNPRG, and negatively related to EXPNORC and FAMLYSIZ.

These results seem counter intuitive except for FAMLYSIZ

and, because of the problems with the American sample, leave

the question open as to which are the salient aspects of the

environment influencing memory.

Spearman's 'g'

Spearman's 'g', or the first principal component, is from

a separate analysis of the cognitive tests. The American

sample Spearman's 'g' has a correlation of .79 with the full

scale from the Wechsler Adult Intelligence Scale. This

factor is virtually the same for both the American and

Korean groups with a congruency coefficient of .95.

SCHOOLWK and READMATH show influence across the AEA and

Korean groups. SCHOOLWK is most related to 'g' for AEAs and

is also important to Koreans. MAGBOOKR shows moderate

influence for both AEAs and AJAs as a group. SES, PARRATG,

and DEVPPREG are important for AEAs. SELFRATG, MOBILITY, and

SOCPARFS are important to AJAs and WEALTH, READMATH,

FAMLYSIZ, and NORCFS are important for Koreans.

The relationship

culture suggests

influences covary

culture to culture.

of

that

with

PAGE 141

'g' to different factors in each

the dynamics of environmental

general abil ity differently from

Influence patterns shown by Spearman's rank correlations

As explained earlier in the Method section, patterns of

influence between environmental variables and cognitive

ability were conceptualized by rank ordering

environment-ability correlations for each of the 15

ethnic-abil ity combinations. Then Spearmanrhos were computed

for similar abilities compared across ethnic groups and for

different abilities compared within ethnic group.

Verbal ability shows the highest rhos across the three

ethnic groups. All three correlations were significant with

the AEA and AJA pattern similarity largest (Rs=.74).

Spearman's 'g' had three significant pattern correlations

with the greatest being the AEA and AJA correlation

(Rs=.69). Spatial and attentional speed also had significant

correlations in each comparison except for AJA with Korean.

Memory abil ity had no significant correlations across ethnic

groups.

The paired comparisons of ability patterns within the

ethnic groups are very high. Spearman correlations between

abilities within the AEA group range from a low of .76

(verbal v s , spatial) to a high of .94 (verbal with

Spearman's 'g'). The range for AJAs is from .41 (verbal with

speed) to .83 (verbal with Spearman's 'g'). Six

of the Rs are significant for Koreans;, again

skill with Spearman's 'g' (.89) being the

PAGE 142

perceptual

out of ten

with verbal

highest.

The two pairings showing high correlations across all

three groups are verbal ability with Spearman's 'g' and

spatial skill with Spearman's 'g'.

The generally higher rhos between abilities within a

given ethnic group than for comparable abilities across

ethnic groups suggest greater diversity in environmental

effects across ethnic groups than across ability factors.

Summary

The focus of this study is on cross-cultural aspects of

environment and how they relate to cognitive abilities. The

analyses are grouped into two main sections. The first

section shows how environmental variables relate and form

dimensions within each ethnic group. The second shows how

the environmental dimensions relate to cognitive abilities

within each ethnic group.

In the first part, similar environmental variables are

factor analyzed for three cultural groups: Americans of

European Ancestry (AEAs), Americans of Japanese Ancestry

(AJAs), and native Koreans. These environmental dimensions

were then compared across ethnic groups by means of

congruency coefficients. In the second part, the

environmental dimensions were then related to cognitive

abil ities by means of multiple regression. Also,

relationships between environment-abil ity patterns are shown

by Spearman's rank correlations.

The general conclusions are:

1) Most environmental factors show high similarities

across ethnic group. Every environmental factor in the AEA

group is mirrored by factors from one of the other two

groups. This means that the environmental relationships

forming factors In one ethnic group or culture (i.e. school

work, socio-economic status, family age, family size, etc.)

generally hold for another ethnic group or culture.

2) Certain factors such as: socio-economic status, school

work, self ratings, and amount of reading show consistently

strong relationships to abilities across groups. Other

factors show relations to abilities within certain groups.

Developmental and pregnancy problems, parental ratings,

years of education and age, a spell ing-math dichotomy, mood

ratings, and a roommate factor all have consistent effects

across abil ities for AEAs. Mobil ity, acculturation, and

social participation are important for AJAs, and family

size, wealth, and a read-math dimension for Koreans.

3) Spearman rank correlations show patterns of

environmental influence more closely related within ethnic

group than across cognitive abil ity. Although not as high as

within group comparisons certain abilities, most notably

verbal and Spearman's 'g', show significantly similar

patterns of influence.

This study has tried to map areas of environmental effect

on cognition as a first step in breaking down the global

concept of environment. Also implicit in studies of this

type is the goal of integrating the components into a

picture of how the environment as a whole acts upon

cognitive abilities. With regard to verbal ability this was

approached by showing the combination of school work, SES,

and reading accounting for the majority of environmental

variance. The picture is less clear for other cognitive

abil ities although a few dimensions show consistency of

effect across ethnic groups.

In any factor analytic study the original choice of

variables acts as a limit on what dimensions will be found.

If many variables covering a certain area are included, this

virtually assures that this area will be reflected by one or

more factors in the results. Conversely a dimension can not

be reflected If the variables pertaining to It are not

included In the analysis. Diverse variables were considered

in this study and a few comments are appropriate. A

distinction may be drawn between variables that an external

observor could record and the subject's self report. Asking

the subject to report ability perferences is far removed

f rom the concept of an env ironment act ing on an Ind Ivi dua 1

and possibly should not be emphasized in building models of

env i ronmen t .

This study, along with previous studies, has tried to lay

a groundwork along which discussions about environment may

proceed. Many environmental dimensions, notably school work,

SES, age, family structure, reading, and developmental and

pregnancy problems have been widely cited in the 1 iterature,

show high similarity across ethnic groups and probably exist

for all industrial ized, urban groups. If investigators

exploring environmental relations in future studies used

marker variables from these major dimensions, different

studies could be more easily compared, evaluated, and

integrated. Also, this approach would gradually bring forth

a consensus among resea rche rs as to the sa 1 i ent aspects of

environment with regard to cognitive abil l t l e s , It would be

possible to see if relations reported in different studies

vere themselves related and/or possibly a subset of a

broader environmental effect.

Certain dimensions (i.e. school work, SES, reading,

developmental and pregnancy problems) presented have both

cross cultural relations with cognitive abil ities and

account for comparatively large amounts of variance. These

are key areas of influence which should be recognized in any

program aimed at improving cognitive abil ities.

Finally, would 1 ike to add my voice to those call ing

for more cross cultural research. Environmental relations

that can be shown to cut across different cultures offer

strong evidence of which dimensions may mediate or control

development of cognitive abilities. Also, studying how

environmental effects differ from culture to culture will

give insight into the concept of intell igence and how it is

fostered differently across cultures. The fabric of

environment is complex, but a start has been made in

defining areas within the environment and showing how they

relate to cognitive abil l t l e s ,

BI BLiOGRAPHY

Altman,In M.Bra i n1971.

J. Nutritional deprivation and neural development.B. Sterman, D. J. McGinty, & A. M. Adinolfi (eds.),develooment and behavior. New York: Academic Press,

Atherton, K. R. A comparison of solutions obtained in factoranalyses of socioeconomic variables. Psychol. Reports~

1962, 11: 259-273.

Altus, W. D. Birth order and its sequelae. Science, 1966,151:44-49.

Bacher, F. Quelques donnees recentes sur les aptitudesverbales. BulletIn de Psychologie, 1966, 19: 642-654.

Bajema, C. J. Estimation of the direction and intensity ofnatural selection in relation to human intelligence bymeasns of the i nt r i ns i c rate of natu ra 1 increase. Euzen ,Qua r t , , 1963, 10: 175 -187 •

Bayley, N. & Schaefer, E. Correlations of maternal and childbehavIors with the development of mental abil ities: datafrom the Berkeley Growth Study. Mongr. Soc. Res. ChildDevelop., 1964, 29: 1-80. .

Becher, W. C., & Krug, R. S. A circumplex model for socialbehavior in children. Child Develop., 1964, 35: 371-396.

Bennett, E. le, Diamon, M. C., Krech, D., & Rosenweig, M.ChemIcal and anatomIcal plasticity of the brain. Science,1964, 146: 610-619.

& Henri, V. La Psychologie individulle. Annee1896, 2, 411-465. Binet, A. & Simon, T. Sur lad'etabler un diagnostic scientifique des etats

de l'intelligence. Annee Psychol., 1905, 11:

Binet, A.psvcho l , ,necessiteenferirurs163-190 (a},

Binet, A. & Simon, T. Methodes nouvelles pour le diagnosticdu niveau Intellectuel des anormaux. Annee Psychol., 1905,11: 191-244(b).

spatialstudy.

Blade, M. F. & Vatson, W. S. Increase InvIsualIzation test scores during engineeringPsychol. Monogr., 1955, 69 (No. 397).

Boring, E. G. Intell l gence as the tests test It. ~Republic, 1923, 35: 35-37.

Breland, H. M. Birth order, familY configuration and verbalachievement. Princeton, N.J.: Educational Testing Service,1972.

Broman, S., Nichols, P., and Kennedy, W. Preschool IQprenatal and earlY developmental correlates, New York:John Wiley & Sons, 1975.

Bronfenbrenner, U. Socialization and social class throughtime and space. In E. E. Maccoby et ale (eds.), Readingsin social psychology (3rd ed.). New York: Holt, Rinehart &winston, 1958.

Buck, C., Gregg, R., Stavraky, K., & Subrahanian, K.Variables associated with social class differences in theintelligence of young childern. Multivar. Behav. Res.,1973, 8: 213-226.

Burt, C. The bearing of the factor theory on theorganization of schools and classes. Report to the L.C.C.Psychologist, 1919.

Byrnes, R. & Henmon, V. Parental occupation and mentalability. J. EdUCt Psycho)., 1936, 27: 284-291. Cattell, J.M. Mental tests and measurements. Mind, 1890, 15: 373-381 ••

Cattell, R. B. Is national intelligence decl ining. Eugen.~' 1936, 28: 181.

Cattell, R. B. The principal culture patterns discoverablein the syntal dimensions of existing nations. J. Soc.Psychol., 1950, 32: 215-253.

Cattell, R. B. Factor analysis: An introduction and manualfor the psychologist and social scientist. New York:Harper & Row, 1952.

Cattell, R. B. The scree test for the number of factors.Mult. Beh. Res., 1: 245-276.

Chapin, F. S. Prel iminary standardization of a socialinsight scale. Am. Soc. Rev., 1942, 7: 214-225.

Coleman, J. S., Campbell, E. Q. , Hobson, C. J., McPartland,J., Mood, A. M., Wainfeld, F. D., & York, R. L. Egualityof educational opportunity (Supt. of Documents Catalog No.FS 5.238). Washington, D. C.: U. S. Government PrintingOffice, 1966.

Cravioto, J. Nutritional deficiencies and mental performancein childhood. In D. C. Glass (ed.), Biology and behaviorenvironmental influences. New York: The RockefellerDnlversity Press and Russell Sage Foundation, 1968. Dave,R. H. The identification and measurement of environmental

process variables that are related to educationachievement. Umpubl ished doctoral dissertation, Universityof Chicago, 1963.

de Candolle, A. Histoire des sciences et des savants depuisdeux slecles, precedee et suivie d'autres etudes sur dessujet sclentifiques en partlculier sur 1 'heredite et laselection dans 1 'espece humaine. Geneve: H. Georg, 1873.

de Montmoll in, M. Le niveau intellectuel des recrues ducontingent (the intellectual level of recruits>.Population, 1958, 13: 259-268.

DeFries, J. C., Vandenberg, S. G., McClearn, G. C., Kuse, A.R., ~Hlson, J. R., Ashton, G. C., & Johnson, R. C. NearIdentity of cognitive structure in two ethnic groups.Science, 1974, 183: 338-339.

Dockrell, W. B.development of36: 7-14

Secondary education, social class and theabil l t l es , Brit. J. Educ. Psychol., 1966,

Douglas, J. W. B. The home and the school. London: MacGibbon& Keen, 1961.

Duncan, O. D., Featherman, D. L., & Duncan, B. Socioeconomicbackground and achievement. New York: Seminar Press, 1972.

Dugdale, R. L. The Jukes. New York G. P. Putnam's Sons,1877.

Ferguson, L. R., & Maccoby, E. E. Interpersonal correlatesof differential abilities. Child Develop., 1966, 37:549-571.

Flanagan, J. C., & Cooley, W. W. Project talent one yearfollow up studies. Pittsburgh, Pa.: University ofPittsburgh, School of Education, 1966.

Flaugher, R. L. & Rock, D. A. Patterns of ability factorsamong four ethnic groups. Proceedings of the 80th AnnualConvention of the American Psychological Associatidh,1972, 7, 27-28.

Galton, F. Hereditary genius: an inquiry into its laws andconsequences. London: Macmillan, 1869.

Garrett, H. E. A developmental theory of intell igence. Amer.Psychol., 1946, 1: 372-378.

Gazzaniga, M. S. & Sperry, R. W. Language after section ofthe cerebral commissures. Brain, 1967, 90, 131-148:

Gorsuch, R. L. Factor Analysis Philapelphia, \'J. B. Saunder

Co., 1974.

Hadden, J. K., & Borgatta, E. F. American cities, theirsocial caracteristics. Chicago: Rand McNally, 1965.

Harlow, J. F. The development of affectional paterns ininfant monkeys. In B. M. Foss (ed.), Determinants ofinfant behavior. New York: Wiley, 1961.

Harrell, R. F., Woodyard, E., & Gates, A. I. The effect ofmothers' diets on the intelligence of the o¥fspring. NewYork: Teachers College, 1955.

Harrell, T. W., & Harrell, M. S. Army general classificationtest scores for civilian occupations. Educational andPsychological Measurement, Autumn 1945, 5: 229-239.

Havighurst, R. J., & Breese, F. H. Relation between abilityand social status in a midwestern community. J. Educ.PsYchol., 1947, 38: 241-247.

Hebb, D. O. Heredity and environment in behavior. in D. E.Dulany (ed.), Contributions to modern psychology. NewYork: Oxford University Press, 1963

Hess, R. D. Class and ethnic influences upon socialization.In P. H. Mussen (ed.), Carmichael's manual of childpsycholo~~. New York: Wiley, 1970.

Higgins, J. V., Reed, E. W., & Reed, S. C. Intell igence andfamily size: a paradox resolved. Eugenics Quarter1y, 1962,9: 84-90.

Hilton, L. L., & Myers, A. E. Personal background,experience and school achievement: an investigation of thecontribution of questionnaire data to academic prediction.J. Educ. Meas., 1967, 4: 69-80.

Honzik, M. P. A sex difference in the age of onset of theparent-child resemblance in intelligence. J. Educ.Psychol., 1963, 54: 231-237.

Humphreys, L. G. & Taber, T. Ability factors as a functionof advantaged and disadvantaged groups. J. of J. Educ.Meas., 1973, 10: 107-115.

Itard, J. M. G. The wild boy of Ayeyron (Rapports etmemories sur le sauvage de 11 averyon) (G. Humphrey & M.Humphrey, trans.). New York: The Century Co., 1932.

Jencks, C., Smith, M., Acland, H., Bane, M., Cohen, D.,Gintis, H., Heyns, B., & Michelson, S. Inequal [tV: areassessment of the effect of familY and schooling inamerica. New York, Harper & Row, 1972.

Jensen, A. R.three ethnic115-125.

PAGE 151

Personality and scholastic achievement ingroups. Brit. J. Educ. Psychol., 1973, 43:

Johnson, R. C. & Medinnus. Child Psychology. New York: JohnWiley & Sons, 1974.

Kagan, J., & Moss, H. A. Parental correlation of child's I.Q. and height: a cross-val idation of the Berekely growthstudy results. Child Develop., 1959, 30: 325-332.

Kah 1, J. A. , &socio-economic317-325.

Davis,status.

J. A. A comparison of indices ofAmer. Sociol. Rev., 1955,20:

Kennett, K. F., & Cropley, A. J. Intelligence, family size,and socioeconomic status. J. Biosoc. Sci., 1970, <:227-236.

Keys, A., Brozed, J., Henschel, A., Mickelsen, 0., & Taylor,H. L. The biology of human starvation C2 vols.).Minneapol is, Minn.: University of Minnesota Press, 1950.

Knupfer, G. Indices of socioeconomic status: a study of someproblems of measurement. New York: Knupfer, 1946.

LeVine, R. A. Cross-cultural study In child psychology. InP. H. Mussen Ced.), Manual of child psychology (Vol. 2).New York: Wiley, 1970.

Lienert, G. A. Die Factorenstruktur der Intelligenz alsFunktion des Intelligenzniveaus. Ber. 22 Kongr. Duetsch.Ges. Psychol., Gottingen, Hogrefe, 1960, 1~8-140.

Lienert, G. A. Uberprufung und genetische Interpretation derDivergenzhypothese von wewetzer. Vita Hu~, 1961, 4:112-124.

Loehlin, J. Llndzey, G., & Spuhler, J. Race differences inintelligence. San Francisco, W. H. Freeman & Co., 1975.

Majoribanks, K. Ethnic and environmental influences onmental abilities. Amer. J. Sociol., 1972, 78: 105-164.

Meili, R., & Steiner, H. Eine Untersuchung zumIntelligenzniveau elfjahriger der deutschen Schweiz (Aninvestigation of the intelligence level of german-swisseleven year olds). Schweizerische Zeitschrift furPsychologle un ihre Anwendungen.

Meyer, C. T. The effects of training in mechanical drawingon spatial relations test scores as predictors ofengineering drawing grades. Research Bull. No. 58-69,

Educational Testing Service, Princeton, J. J., 1958.

Michael, W. B. Factor analysis of test and criteria: Acomparative study of two AAf pilot populations.Psychological Mono., 1949, 63 (whole No. 298)

Milner, E. A.read i ness inparent-ch i 1d95-112.

A study of the relationship between readinggrade one school children and patterns ofinteraction. Child Develop., 1951, 22:

Moore, T. Language and intell igence: a longitudinal study ofthe first eight years, environmental correlates of mentalgrouth. Human Develop., 1968, 13: 259-268.

Moser, C. A., & Scott, W. British towns. Edinburgh: Oliver &Boyd, 1961.

Moss, H. A., & Kagan, J. Maternal influences on early I. Q.scores. Psvcho l , Rep, , 1958.

Mosychuk, H. Differential home environments and mentalpatterns. Unpubl ished PhD. Thesis, University of Aberta,1969.

Murdock, G. P. World ethnographic sample. Amer. Anthrop.,1957, 59: 664-687.

Nuttin, J. De verstandel ijke begaafdheid van de jeugd in deverschillende soclale klassen en woonplaatsen (Primarymental abilities in children as related to parentaleducational and occupational level, rural-urban livingconditions, and ses). Mededellngen konlnkl Vlaamse Acal.Wetensch. Lett. Schone Kunsten Belgle, Klasse Lett. 27 No.7 Brussesl, 1965.

Nuttin, J. Classe sociale, dimension de la famille etaptitude intellectielle (Social class, family size andintellectual abil ity). L'Annee Psvcho l , , 1970, 70:467-485.

Olive, H. The relationship of divergent thinking tointelligence, social class, and achievement in high schoolstudents. J. Genet. Psych., 1972, 121: 179-186.

Park, J. Y. A study of multivariate cognition in Korea inrelation to environmental and hereditary influences.Unpublished doctoral dissertation, University of Hawaii,1975.

Pearson, Karl Early statistical papers. Cambridge: CambridgeUniversity Press, 1948.

Poole, A., & Kuhn, A. Family size and ordinal position:

correlates of academic success. J. Biosoc. Sci., 1973, 5:51-59.

Porteus, S. D. The practice of c1 inical psychology. NewYork: American Book, 1941.

Ranucci, E.aspectsdoctoral1952.

Effect of the study of sol id geometry on certainof space perception abilities. Unpublisheddissertation, Columbia University, New York,

Reiss, A. J. Occupations and social status. New York: FreePress, 1961.

Rummel, R. J. Applied factor analysis Evanston: NorthwesternUniversity Press, 1970.

Rummel, R. J. The dimensions of nations. Beverly Hills: SagePublications, 1972.

Sampson, E. E. The study of ordinal position: Antecedentsand outcomes. In B. A. Maher (ed.), Progress inexperimental personal ity research (Vol. 2). New York:Academic Press, 1964.

Sargent, S. S., & Stafford, K. Basic te~chings of the greatpsychologists. New York: Doubleday & Co., 1965.

Sawyer, J., & LeVine, R. A. Cultural dimensions: a factoranalysis of the world ethnographic sample. Amer. Anthrop.,68: 708-731.

Schaefer, E. A. Development of parental attitude researchinstrument. Child Develop., 1958, 29: 339-361.

Schull, W. J., & Nee1, J. V. The effects of inbreeding onJapanese children. New York: Harper & Row, 1965.

Schultz, D. P. A history of modern psychology. New York:Academic Press, 1969.

Scott, J. P. & Fuller, J. L. Genetics and the socialbehavior of the dog. Chicago: University of Chicago Press,1965.

Scottish Council for Research in Education. The inte11 igenceof Scottish children a national survey of an age group.London: University of London Press, 1933.

Semmes, J. Hemispheric special ization: a possible clue tomechanism. Neuropsycho1ogia, 1968, 6' 11-26.

Sharp, S. E. Individual psychology: a study in psychologicalmethod. Amer. J. Psycho1., 1898-99., 10: 329-91.

Siegel, s. Nonparametric statistics for the behavioralsciences. New York: McGraw-Hill, 1956.

Skeels, H. M. Adult status of children with contrastingearly life experience. Monogr. Soc. Res. Child Develop.,1966, 31: 1-65 (serial no. 105>'

Spearman, C. The proof and measurement of associationbetween two things. Amer~ J. Psychol., 1904, 15: 72-101.

Spearman, C. "General intell igence" objectively determinedand measured. Amer. J. Psychol., 1904, 15: 201-293.

Spearman, C. The abilities of man. New York: Macmillan,1927.

Stein, Z., Susser, M., Saenger, G., & Marolla, F. Nutritionand mental performance. Science, 1972, 178: 708-713.

Stern, W. Uber dieIntellegenzprufung. Ber16: 1-109.

psychologischen Methoden derV. Kongress expo Psychol., 1912,

Stevens, S. S. The operational definition of psychologicalconcepts. Psych. Rev. 1935, b. 42, 517-527.

Stewart, N. "AGCT scores of army personnel grouped byoccupation." Occupations 26, 1947, 5-41.

Svensson, N. E. Ability grouping and scholastic achievement.Stockhol,: Almqvist and Wiksell, 1962.

Tanner, J. M. Regulation of growth in size in mammals.Nature, 1963, 199: 845-850.

Terman, L. M. The measure of intelligence: an explanation ofand a complete guide for the use of the Stanford revisionand extension of the Binet-Simon intelligence scales.Boston: Houghton Miffl in Co., 1916.

Terman, L. M. "Trails to psychology." In C. Murchison (ed.),A history of psychology in autobiography (Vol. 2).Worcester, Mass.: Clark University Press, 1932.

Thomson, G. H. The factorial analysis of human abil ity (5thed.). Longon: University of London, 1951.

Thorndike, E. L. Your city. New York: Harcourt, Brace & Co.,1939.

Thorndike, E. L. "Constancy"of I.U. Psychol. Bull., 1940.33: 267-286.

Thurstone, L. L. Primary mental abi 1i ties. Chicago:University of Chicago Press, 1938.

Thurstone, L. L. Chapter in Murchison, C. (ed.). A historyof psychology in autobiography (Vol. 4). Worcester, Mass.:Clark University Press, 1952.

Tryon, R. C.alternative43: 425-454.

A theory of psychological components - anto mathematical factors. Psychol. Rev., 1935,

Tuddenham, R. D. The nature and measurement of intelligence.In L. Postman (ed.), Psychology in the making. New York:Alfred A. Knopf, 1962.

Vandenberg, S.i nher i tance ofCancro (ed, ),Inc., 1971.

G. What do we know today about theintelligence and how do we know it? In R.

"Intelligence". New York: Grune & Stratton

Vandenberg, S. G. Environmental influences on abilities andmethods for assessing them. Unpublished manuscript,University of Colorado, 1975.

Vernon, P. E. Intelligence and cultural environment. London:Methuen, 1969:=

Wechsler, D. The measurement of adult. intelligence.Blatimore: Williams & Wilkens, 1944.

Wechsler, D. Manual for the Wechsler intelligence scale forchildren. New York: The Psychological Corp., 1949.

Werner, E. E., Bierman, J. M., & French, F. E. The childrenQf Kauai: a longitudinal study from the prenatal period toage ten. Honolulu: University of Hawaii Press, 1971.

~Jilson, J., DeFries, J., McClearn, G., Vandenberg, S., &Johnson, R. Cognitive abilities: use of family data as acontrol to assess sex and age differences in two ethnicgroups. Aging and Human Development (in press).

Wi 1son, K.offspring.Hawa i i •

W. Environmental correlates of cognition forUnpublished manuscript, 1975. University of

Wissler, C. "The correlation of mental and physical tests".The Psychological Review Mongraph Supplements 3, No.6(whole no. 16) 4, 27, 29, 34-36 (1901>.

Wolf, R. M. The identification and measurement ofenvironmental process variables related to intelligence.Unpublished doctoral dissertation, University of Chicago,1964.

Zajonc, R. B. Family configuration and intelligence.Science., 1976, 192: 227-236.

Zigler, E. & Child, I. L. Socialization in Vol. III. In G.Lindzey and E. Aronson (eds.), Jhe handbook of socialpsychology, 2nd edition. Reading, Mass.: Addison-Wesley,1969.