RESEARCH METHODS PART 5

DATA COLLECTION Decisions which the researcher makes regarding the sources of information about the study. The researcher considers whether there are data already available in one form or another or whether he must gather new data.2 TYPE OF DATA1.PRIMARY2.SECONDARY

PRIMARY DATA-New data can be gathered according to the researchers own specifications in line with his particular objectives. Generated by either questioning people thought on the desired behaviour, or by observing selected activities. Questioning through:Mail SurveyPersonal InterviewFocus GroupDelphi TechniqueProjective Techniques

SECONDARY DATAAlternatively, there are many kinds of available information that the researcher can used:Public RecordsPrevious StudiesCompany Documents/Annual ReportsPublished Data Government DocumentsTrade PublicationsBooks- Also may include the thoughts of non-observer.

TRIANGULATIONThe combination of methodologies in the study of the same phenomenon. May be based upon: Collection of different kinds of data Multiple viewpoints allows for greater accuracy Validation process to ensure that the variance reflected that of the trait rather than the method.

They might relate to the following:ScaleReliabilityConvergent Validation

Triangulation in Organizational Research: Refers to the use of multiple methods to examine the same dimension of a research problem, eg.The effectiveness of a manager may be studied by interviewing, observing, and by reviewing performance records.

INSTRUMENT AND MEASUREMENTSIf a variable exists, it exists in some amount. If it exists in some amount, it can be measured - Two principle issues confront all measuring instrument:Is it Reliable?Is it Valid?

INSTRUMENTATIONIt is the process of selecting or developing measuring devises and methods appropriate to a given evaluation problem.

Specifically, instrumentation refers to: -Questions to be asked in order to tap thevariables/concept -To determine to what extent subjective feelings, attitudes, or perceptions might exist in different individuals. -Developing or selecting instruments to measure the responses.

MEASUREMENT It is the process of assigning numbers to represent the properties of persons, objects, events, or states. These symbols are to have the same relevant relationships to each other as do the things represented. The empirical definition if measurement does not refer to the theoretical component of the measurement process Measurement considerations may help to clarify the theoretical thinking and to suggest new variables that are to be considered. Careful attention to issues of measurement may force a clarification of ones basic concepts and theories. Measurement involves an explicit, or organized plan for classifying (and quantifying) the particular data at hand in terms of the general concept in the researchers mind.

4 CLASSES OF MEASURES PHYSICAL TRACESVery Indirect.Indicators of psychological and social processes.Most prone tomisinterpretation. ARCHIVESDocuments and Records. Not to be taken at facevalue. SIMPLE OBSERVATIONWho spoke to whom.Position and spatial arrangement. Facial and postural clues, Nonverbal cues. HARDWARE Photographs etc.

SCALES

A scale is an internally consistent plan for developing a measure. The concern is to develop a valid and reliable set of indicators of the theoretical constructs. A tool of mechanism by which individuals are distinguished based on the variables of interest. The type of scale achieved when we deputize the numerical to serve as representatives for a state of affairs in nature depends upon the character of the basic empirical operations performed on nature.

SCALES should composed of multiple items rather than single item because: More likely to represent a complex theoretical concept or attribute. Single-item measures lack precision because they cannot discriminate among fine degrees of an attribute. Single-item scales usually are less reliable than multi-item scales Single-item scales provide only a single measurement, preventing an assessment of their measurement properties.

TYPES OF SCALING METHODS1. SUBJECT-CENTERED APPROACHExamines systematic variation across respondents.All systematic variation is attributed to differences among subjects.2. STIMULUS-CENTERED APPROACHExamines systematic variation across stimuli.Variations across subjects controlled or measured (homogeneous subjects)3. RESPONSE APPROACHExamines subject and stimuli systematic variations.

FOUR BASIC SCALE METHODS1. NOMINAL Equality for placement in the classes.2. ORDINAL greater than or less than for objects.3. INTERVAL Equality of differences between intervals.4. RATIO True zero point.

Each classes of scales:Differentiate by the range of variance, andSets limit to the kind of statistical manipulation that can legitimately be applied.

Nominal Scale : y=f(x)The objects are assigned to mutually exclusive labeled categories, but there are no necessary relations among the categories i.e. no ordering or spacing is implied if one entity is assigned the same number as another, they are identical with respect to a nominal variable. Otherwise, they are just different e.g gender, geographic location, and marital status are nominally scaled variables. The only arithmetic operation that can be performed on such a scale is a count in each category.PERMISSABLE STATISTICS INCLUDE;Mode, contingency coefficient.

Ordinal Scale: y=f(x)This scale is obtained by ranking objects, or arranging them in order with regard to some common variable. The question is whether each object has more or less of this variable than some other object. However, no spacing is implied so the permissible arithmetic operations are limited to statistics such as the median or mode, but not the mean. The finishing order in a horse race or class standing illustrate this type of scale. Similarly, brands of frozen vegetables can be ranked according to that -- from highest to lowest.

Interval Scale: y=a +bx, where b>0Here, the numbers used to rank the objects also represent equal increments of the attribute being measured. This means that differences can be compared. The difference between 1 and 2 is the same as 2 and 3, but is only half the distance from 2 and 4. However, the location of the zero point is not fixed since zero does not denote absence of the variable, rg. Temperature.Farenheit and Celsius temperatures are measured with different interval scales and have different zero points. Interval scales have very desirable properties because virtually the entire range of statistical operations can be employed to analyze the resulting numbers, including addition and subtraction. A recurring question of most attitude measures is whether they are interval scales. Usually, it is doubtful that the intervals betweenm categories are exactly equal, but they may not be so equal as to preclude treating it as an interval scale. A good example is a willingness to buy scale with ten categories labeled from 1 to 10. If this were an interval scale, we could say that two people with scores of 2 and 4 respectively differed by the same degree of willingness as two other people with scores of 8 and 10.

Ratio Scale: y=cX, where c>0This is a special kind of interval scale that has a meaningful zero point. With such scales eg.weight, market share, or dollars in saving accounts; it is possible to say how many times greater or smaller one object is than another. A score of 4 is two times a score of 2. Obviously, attitude scales cannot achieve this property.

ATTITUDE SCALES

SCALE is essentially, a measuring devise allowing the assignment of symbols or numbers to individuals, or their behaviour. By rule, such an assignment indicates the individuals possession of a corresponding amount of whatever the scale is claimed to measure.-All methods of observation are inferential,varying in the degree of objectivity they posses.

TYPES OF ATTITUDE SCALE1. Summated Rating Scales/Likert Scales2. Equal-Appearing intervals/Thurstone Scales3. Cumulative Scales/Quttman Scales4. Semantic Differential scales

TYPES OF ERRORS

HALO EFFECT: Tendency for an irrelevant feature to influence eg. Firstimpression RATING ERROR: Over-rater, under-rater, central tendency. HAWTHORNE EFFECT: Under study, novelty, modified environment, knowledge of results. SELF-FULFILLING PROPHESY: What the researcher expects. JOHN HENRY EFFECT: Those in the control group are determined to proof or to show the experimental group. PLACEBO EFFECT: Expectations and Suggestibility. Natural stimulus given as it were the active treatment. POST HOC ERROR: Assumption about cause-effect relationship. LAW OF THE INSTRUMENT: Using a certain instrument as a means ofsolving all problems.

VALIDITY Is the instrument measuring what it claims to measure, is it relevant? Validity is defined as the extent to which any measuring instrument measures what it is intended to measure Concept of REALISM.The Realism of a certain set of data consists of its correspondence to some facts its truth.The Realism of a certain set of data consists of its connection with some significant problem or with the purpose of the study - its relevancy.One validates not the instrument, but the interpretation of data arising from the specified procedure. The focus of validity should be to ensure that the measurement used is related to an indication of the response expected, or the specific criterion which it is supposed to predict.

TYPES OF VALIDITY TO BE CONCERNED WITH:Statistical Conclusion ValidityInternal ValidityConstruct ValidityExternal Validity

1. CONTENT VALIDITY:Does the content (items) adequately i) Face Validitymeasure the concept? The more items, the greater the validity.2. CONSTRUCT VALIDITY: Does the instrument tap the concept asexpectedi) Convergentii) DiscriminantSome degree of agreed upon accuracy.3.CRITERION-RELATED VALIDITY: Does the measure differentiate in a manner that helps to predicti) ConcurrentThe scale discriminates the differences4.EXTERNAL VALIDITY:The extent of generalization of the resultsof a causal study to other field setting.

RELIABILITY Is the measuring instrument accurate, consistent, and stable? Reliability concerns with the extent to which any measuring procedure yields the same results on repeated trials (Time-Associated and Form-Associated). Estimates of reliability are derived based on:Average Correlation among Items (Internal Consistency) in the measuring instrument. It is identified with truth. Reliability is a necessary, but not a sufficient condition for validity. Reliability of a measurement with respect to a given variable, means the constancy of its results as that variable assumes different values. The variables usually considered are: The measuring event (eg. same person using the same ruler in successive measurements of the same object). The measuring instrument (rg. Different forms of an intelligent test). The person doing the measuring (eg. different eyewitnesses of the same event). Repeated measures with the same instrument on a given sample of data should yield similar results.

3 KINDS OF RELIABILITY1. STABILITY: Degree to which a process is invariant over time, ie. Yields the same results at different points in time.2. REPRODUCIBILITY: Degree to which a process can be recreated under varying circumstances, different locations, involving different material forms, ie. Yields the same results despite different implementations.3. ACCURACY: Degree to which a process conforms in effect to a known standard, ie. Yields the desired results in a variety of circumstances.

PILOT STUDYStudy done in advance of the big study to find out how the respondents actually think or talk about the topic of interest.Before a questionnaire is ready for use, it has to be pretested. The purpose of the pretest is to check whether the ideas in each question are clear to the respondent.The pretest may show that some questions should be reworded, or in the case of multiple-choice questions, different or additional alternatives may have to be included.The participants in the pilot should be similar to those who will be included in the actual study.If, after the pilot, a number of significant revisions are made, a second pilot may be necessary.