casual comparative research

8/13/2019 Casual Comparative Research

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Dr. Ayaz Muhammad Khan Assistant Professor

University of Education, Lahore


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Causal Comparative ResearchDetermine the cause of existing

differences among groups.

The Aim


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DefinitionIt is a quantitative researchTo determine the cause or consequences of the

differences that already exist between or among groupof individuals- ex post facto


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Description At least two different groups are compared on adependent variable or measure of performance (calledthe effect) because the independent variable (calledthe cause) has already occurred or cannot bemanipulated.Dependent variable -the change or difference

occurring as a result of the independent variable.Independent variable- an activity of characteristicbelieved to make a difference with respect to somebehavior.


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CharacteristicThe researcher attempts to determine the cause, orreason, for pre existing differences in groups ofindividuals. Attempts to identify cause and effect relationships.Involve two or more group variables.Involve making comparison.Individuals are not randomly selected and assigned totwo or more groups.Cannot manipulate the independent variableLess costly and time consuming


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StepsTaken

1. Problem2.Sample

3.Design andprocedure4.Data

Analysis


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ProcessProblem formulationIdentify and define particular phenomena of interest andthen to consider possible causes for, or consequences of these

phenomenaSampleDefine carefully the characteristic to be studied and selectgroup that differ in this characteristic

InstrumentationNo limitation

DesignInvolve selecting groups that differ on particular variable ofinterest, compare and remember no manipulation!


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DESIGN

Select two groups that differ on some independent variable I.One group possesses some characteristics that theother does not II.

Each group possesses the characteristic but in differingamounts


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The Basic Causal-Comparative Designs

Independent DependentGroup variable variable

(a) I C O(Group possesses (Measurement)

characteristic)II C O

(Group does (Measurement)not possess

characteristic)

(b) I C1 O

(Group possesses (Measurement)characteristic 1)

II C2 O(Group possesses (Measurement)characteristic 2)


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Examples of the Basic Causal-Comparative Design

(Figure 16.1)


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Cont.Data Analysis

Construct frequency polygons

Calculate means and standard deviationsT-test to show differences between meansThe result do not prove cause and effect, but onlyidentifying the relationship


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Example: The Relationship between Years of

Experience and Job SatisfactionCausal Comparative DesignHypotheses Alternative- Teachers with a high level of experience will be more satisfied with their jobs than teachers with low levels of experience. Null- Teachers with a high level of experience will beequally satisfied with their jobs when compared toteachers with low levels of experience.

VariablesDependent- Job satisfaction

Independent- Years of experience


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Two levels (high & low)

Exists naturally in the population of teachers at thestart of study.Sample

Two groups sampled, one for each level of the

independent variableHigh ExperienceLow Experience


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Design and Procedure Select two groups that differ on some independent variableOne group possesses some characteristic that the otherdoes notEach group possesses the characteristic but in differingamountThe independent variable must be clearlyoperationally defined* Randomly sample subjects from each of the twogroupsCollect background information on subjects todetermine the equality of the groups Compare groups on the dependent variable


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Design and Procedure

Control of Extraneous variable What other variable besides years of experience couldexplain job satisfaction among teachers?Matching: Each subject in the high experience group ismatched with a subject with a low experience groupalong the variable of class size.Each high experience teacher who teachers a largeclass is matched with a low experience teacher whoteaches a large class.Each high experience teacher who teaches a smallclass is matched with a low experience teacher who

teaches a small class.


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Data AnalysisMean- job satisfaction ratings for High Experience andLow Experience subjects are compared using t-test, ANOVA or other appropriate statistical test.

Rejection of the null hypothesis supports thealternative hypothesis that years of experience result inincreased job satisfaction.


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THREATS TO INTERNAL VALIDITY IN

CAUSAL COMPARATIVE RESEARCH WEAKNESSES:

Lack of randomizationInability to manipulate an independent variableLoss of subjectsLocationInstrumentationHistoryMaturation


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Cont.Data collector biasInstrument decay

AttitudeRegressionPre-test/treatment interaction effect


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WAYS OF CONTROLLING

EXTRANEOUS VARIABLESMatching of SubjectsFinding or Creating Homogeneous Subgroups

Statistical Matching


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EVALUATING THREATS TO

INTERNAL VALIDITY Step 1: ask: What specific factors either are known toaffect or may logically be expected to affect the variable on which groups are being compared? Step 2: ask: What is the likelihood of the comparisongroups differing on each factor? Step 3: Evaluate the threats on the basis of how likely

they are to have an effect.

casual comparative research

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