research variables (chapter 5)

RESEARCH

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Chapter 5

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One of the most important concepts in research is the concept

of “variable”. There are many kinds of variables and many research studies

involve the examination of relationship

between variables. Variables may be

studied one at a time or in relation to other variables. On this chapter,

variables are defined, classified and

differentiated.

Examples are also given.

CAUSE & EFFECT

ANTECEDENT

INDEPENDENT VARIABLE

VARIABLESREASEARCH I

DEPENDENT VARIABLE

LEARNING OBJECTIV

ESINTERVENING

After studying this chapter, the learners should able to:

Define what a variable is and explain its uses in research.Describe and compare the different types of variables and give examples of each, and Identify the variables on a given study and determine the nature of relationshipbetween them.

A variable is a concept that stands for a variation within a class of objects or persons (Fraenkel and Wallen, 1996).

A variable is a characteristics or property that can take different values or attributes (Schutt, 1999).

Research IChapter 5

Variables

Variables are the basic elements which are measured in a study.

They are observable and measurable.

Research IChapter 5

Variables

ResearchI

Chapter5

Examples of VariablesAgeSexMarital statusIncomeLocation of businessRevenueType of work

Number of meetingsDegree of malnutrition Level of fertilizerType of

cropSize of land

ANTECEDENTINDEPENDENT

DEPENDENT INTERVENING

Variables can be classified as:

The dependent variable is the “assumed effect” of another variable. It is change that occurs in the study population when one or more factors are changed or when an intervention is introduced.

Usually dependent

variable is the problem itself.

Research IChapter 5

Dependent Variable

The independent variable is the “assumed cause” of a problem. It is an assumed reason for any “change” or variation in a dependent variable. An independent variable is sometimes treated as “antecedent” variable (the variable before).

Research IChapter 5

Independent VariableLikewise, an

“antecedent” variable may be

treated as an “independent”

variable.

Examples No. 1In the study on “ The

Relationship Between Exposure to Mass Media and Smoking

Habits among Young Adults”, the dependent variable is “smoking habits”, while the independent variable is “ exposure to mass

media”. A person’s smoking habit is assumed to change or vary

depending on his/her mere exposure to print or broadcast

media related to smoking.

Exposure to Mass Media

Smoking

Habits

Independent Variable

dependent Variable

Examples No. 2In the experimental study to test the “ Effect of Peer Counseling on the Students’ Study Habits”, the

independent variable is “ exposure to peer counseling”. It is assumed that students who have been counseled by peers

will have better study habits that those who were not counseled by

peers or those who have been exposed to traditional counseling

techniques.

Exposure to Peer

Counseling

Study Habits


dependent Variable

Examples No. 3In the study entitled “Factors that

Influence of Extent of Participation in Household

Decision-making among Married Professionals”, the dependent

variable is “the extent of participation in household decision” making while the

independent variable is “factors”, which include the personal

characteristics of the respondents, such as age, sex,

educational attainment and income.

Factors:

Sex. Education

, Age. Income

Extent of decision-making

Participation


dependent Variable

The intervening variable is a factor that works “between” the independent and dependent variables. It can weaken (decrease) or strengthen (increase) the effect of the independent on the dependent.

Research IChapter 5

Intervening VariableIt is also called

a “facilitating variable”,

“moderator” or a “control variable”.

Examples No. 1In the study on “ Knowledge of

the Dangers of Smoking, Attitudes towards Life, and Smoking Habits of Young

Professionals”, the intervening variable is the “attitude towards

life”. A person’d attitude may increase or decrease the

influence of “knowledge on dangers of smoking (independent

variable) on “smoking habits” (dependent variable. Knowing

the dangers in smoking, one may shun smoking.

Cont’d…One may argue, however, that knowledge about the dangers of smoking may not necessarily prevent a person from smoking if he does not mind dying early as long as he/she enjoys life.

Knowledge of the dangers

of smoking

Attitudes towards

life


dependent Variable

Smoking Habits

InterveningVariable

Examples No. 2In the study on “Factors that

Influence Household Decision –making Participation of Married Professionals”, the intervening

variable “gender sensitivity” may affect the relationship between “selected factors” (independent variables) and “decision-making

participation” (dependent variable). Men are generally expected to participate in

decision-making more than women because f social

prescription.

Cont’d…Older, better educated individuals and those with big income are also expected to participate more actively in decision-making than their younger less educated counterparts. It may also be possible that a woman with a gender sensitive partner may also be actively involved in decision-making, despite poor education or low income.

Factors:Sex,

Education, Age,

Income

Gender Sensitivi

ty(Perception

about gender roles)


dependent Variable

Decision-making

Participation

InterveningVariable

Examples No. 3In the study on “ The Effect of

Information Education Campaign (IEC) on Land Reform on the

Farmer’s Attitude Towards land Reform”, the “length of a farmer-

landlord relationship” is the intervening variable. It is

assumed that this variable can strengthen or weaken the

relationship between “exposure to IEC materials” (independent

variable) and “attitudes towards land reform” (dependent

variable).

Cont’d…A farmer may have read or heard about the benefits of land reform, but still reject it (negative attitude) because of a long and close relationship with his landlord and his family which he does not want to be “cut off” by land.

Exposure to IEC

Materials on

Land Reform

Length of Farmer-

Landlord Relationshi

p


dependent Variable

Attitudes Towards

Land Reform

InterveningVariable

The antecedent variable is a factor or characteristics which is found before (ante) the independent variable. It is expected to influence the independent variable/s.

Research IChapter 5

Antecedent Variable

It is usually irreversible.

Examples No. 1In the study entitled “ Attitudes

Towards Land Reform and Acceptance of the Program among Lowland Farmers of Northern Luzon”. The major concern of the study is the

influence of “attitude towards land reform” (independent variable) on the “farmer’s

acceptance of the program” (dependent variable).

Cont’d…The farmer’s attitude towards land reform is expected to vary according to their “education, tenurial status and the size of the land they own” (antecedent variable). More educated farmers who own their farm lots and are tilling more than a hectare of land may be more receptive of land reform than the less educated farmers and those who do not own any farm land or those who own less that a hectare lot.

Education, Tenurial Status,Size of Land

Owned

Attitudes towards

Land Reform


dependent Variable

Acceptance of Land Reform

program

antecedentVariable

Examples No. 2In the study entitled “ Extent of

Exposure to Print Media and Reading Ability of College

Freshmen”, the main concern is the relationship between

students’ “ extent of exposure to print media” (independent variable) and their “reading

ability” (dependent variable). The students’ exposure to print

media, however, may depend on their sex, residence and their

parents’ education (antecedent variable).

Sex, Residence, Parents’ education

Extent to Exposure to Print Media


dependent Variable

Reading

Ability

antecedentVariable

Some researchers cannot answer their research questions because they do not have clear

measures of their variables. A variable must be

OPERATIONALLY DEFINED according to how it is used

in the study, so that it can be

properly measured.

Cont’d…

The operational definition gives a specific meaningto the variable. The definition clarifies how a variable or a term is used and measured inTerms of events/units of measurement that are observable by the senses (Fisher, et al., 1994).These events/units of measurement serve as indicators of the variable.

Cont’d…

The operational definition of a variable specifies how a variable or a term is interpreted in the study and also sets the procedure for measuringVariable. An operational definition of a variable used in one study may differ from that employed in another study.

Variables

1. Age

Indicator/Operational Definition

This refers to the length of time was a person has lived he/she was born. In this study it refers to the age of a respondent on his/her last birthday.

Variables

2. Educational Attainment


This refers to the

highest grade/y

ear complet

ed by respond

ent.

1. Age

This refers to the length of time was a person has lived he/she was born. In this study it refers to the age of a respondent on his/her last birthday.

Variables

2. Educational Attainment3. Exposure to smoking information Campaign


This refers to the

highest grade/y

ear complet

ed by respond

ent.

This means whether or

not the respondent has heard or read about the anti-smoking

campaign and the number of times he/she

has heard/read

the message/s.

Variables

3. Exposure to smoking information Campaign4. Knowledge about smoking

Indicator/Operational DefinitionThis means whether or

not the respondent has heard or read about the anti-smoking

campaign and the number of times he/she

has heard/read

the message/s.

This is represented by the total number of

correct answers in

10-item questionnaire on smoking

and it’s danger

MUTUALLY EXCLUSIVE

CATEGORIESREASEARCH I

VARIABLE

Establishing categories of

variablesEXHAUSTIVE

In some cases, a number , an amount, or a score may not

be sufficient to represent a variable. To facilitate description

and analysis of data, categories

of variables can be established. Each category should also be

operationally defined. The categories must be

mutually exclusive and exhaustive.

Mutually exclusive categories do not overlap. Categories are mutually exclusive when a respondent cannot be assigned to more than one category.

Chapter 5

Mutually exclusive Categories

Some variables, like knowledge scores, can be grouped and each group assigned to a category such as “high level knowledge”, “average level of knowledge” and “low level of knowledge”. Each of these level categories should also be operationally defined.

Example No. 1If for instance, the operational definition of level of knowledge about cancer is “ the number of questions about cancer which a respondent answered correctly”, each level of knowledge may be

assigned a range of scores. Assuming that the total possible

score is 20, the possible categories could be:

High Level of Knowledge= scores of 14 to

20Average Level of Knowledge=

scores of 7 to 13

Low Level of Knowledge= scores of 0 to 6

Cont’d…In the example above the categories are mutually exclusive because a respondent with a score of 15 can be assigned only to “high level knowledge”. However, if scores are decimal numbers, the score limits of each level should be specified, like, “0 to 6.5”, 6.6 to 13.5” and “13.6 to 20”.

Example No. 2For a variable like “residence”, if

its operational definition is” geographical characteristics of the area where the respondents

permanently reside”, the possible answers may be categorized as

“rural” and “urban”. The meaning of “rural” and “urban” , however, may be different in other studies.

The operational definition depends on how the word is used and measured in the study. The categories may be defined as:

RURAL=refers to a place of

residence which is located outside the geographical jurisdiction of a city

or a town center.URBAN=refers to a place of

residence which is located within the town

proper of a municipality.

Categories are exhaustive if all the possible response are included among the options of responses. The answers given by every respondent can be assigned to a particular category. If a researcher is not sure about the exhaustiveness of the categories identified, he/she should include “Others”, the “catch all” category.Chapter 5

Exhaustive Categories

Under this category, responses which can not assigned to any of the other categories can be classified.

Example A list of categories like:

“Protestant, Catholic, Muslim and Buddhist” for responses to a

question on religion is not exhaustive because a Mormon

cannot be classified under any of the categories in the list.For instance, the variable "hobbies” is operationally

defined as “a type of activity a person engages in during leisure

or free time”.

Cont’d…The possible categories of this variable may be: “singing”, “reading”, “painting “writing poems”, “sewing”, “Others, specify”. What may not be classified under the five specific categories can be classified under “Others". However, if during data analysis, the number of responses falling under “others” exceed three, the responses must be specified and based on these an additional category can be

added.

There may be terms in the study (not variables) that

have meanings different from their “dictionary meaning” or

they take on different meanings, depending on situations or

events. These terms must also be defined operationally to

avoid misinterpretation. The definition depends on how the

word is used and measured.

Examples:

1.Family Planning User

Is any currently married woman aged 15 to 49 years old or a married man aged 15 or older who has used a method to prevent or space pregnancy at least once during the last three months.

2. Coastal Barangay

Is a village or

community which is located near the

sea where fishing is the main activity of

the residents.

Examples:

3. Merging

Is the absorption of one or more

business firms by another existing

firm which retains its identity and takes over the

right, privileges, franchises, and properties and assumes all the

liabilities or obligations of the absorbed firm/s

(Pudadera, 2001).

Examples:

4. Interest Rate

Represents the cost of borrowing

money, expressed as

a percent rate, for a

given period of time.

Examples:

MUTUALLY EXCLUSIVE

CATEGORIESREASEARCH I

VARIABLE

HOW TO MAKE OPERATIONAL DEFINITIONS

EXHAUSTIVE

1. List your independent, dependent and intervening (if any) variables.2. Write an operational definition of each variable.

3. Identify the possible categories of each variable and determine if the categories can be clearly understood, are mutually exclusive (do not overlap) and exhaustive. The list of categories is complete so that all respondents can be categorized.

4. List the key terms which may be interpreted differently by different people, unless they are operationally defined. Write an operational definition of each term.5. When defining a variable or a term, be guided by the following questions:

a. Does the definition clearly specify the way the variable will be measured?

b. Are the categories of each variable mutually exclusive?

c. Are the categories exhaustive?

EXHAUSTIVE

ANTECEDENT

INDEPENDENT VARIABLE

VARIABLESMUTUALLY EXLUSIVE

DEPENDENT VARIABLE

evaluationINTERVENING

A. Key terms to Remember

VariablesIndependent VariableDependent VariableIntervening VariableAntecedent Variable

Nominal VariableOrdinal VariableInternal and Ratio VariablesRelationships/Associations

B. Questions for Discussion

1. What are variables?2. What are the different types of variables and how do they differ from each other? Give at least two examples of each type.3. How can you measure a variable? Illustrate using the problem you have selected to study.

C. Exercise

1. Select two relational studies in the list below (next slide) and identify the variables in each of the following research problems.

2. Illustrate in a diagram the possible connections between the variables of each study. Indicate with an

arrow the direction of assumed relationship between the variables.

Cont’d…

3. Write an operational definition for each variables.4. Indicate all the possible categories of responses for each variable.5. Select a variable among those you have defined, the categories of which still need operational definition. Then define the categories.

Problems“The Relationship Between Educational Attainment and Fathers’ Involvement in

School Activities of their Children”

“The Experience with Sexual Harassment of Rank and File

Employees In selected Government Offices”

Cont’d…

“The Effect of Training in Total Quality Management on the Management Skills of Middle Level Managers of Medium-

Sized Establishment in region IV”

research variables (chapter 5)

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