Download - 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.