1. Causal Comparative Research Design

2. Introduction to Causal-Comparative Research
A causal-comparative study is
a study in which the researcher attempts to determine the cause, or reason, for pre-existing differences in groups of individuals
called an “ex post facto” study because both the effect and the hypothetized cause have already occurred and must be studied in retrospect.

3. The aim of causal-comparative research is to determine the cause of existing differences among groups.
Correlational research involves collecting data on TWO or more variables on ONE group;
Causal comparative research involves the collection of data on ONE independent variable for TWO or more groups.

4. The basic causal-comparative research begins with a noted difference between two groups and the causes for or consequences of this difference is looked for
Can be an alternative to experiments.
E.g. If conducting the experiment is costly or time- consuming, you can find groups that are already using what you want to test and conduct a causal-comparative research.

5. Important points to know
Exact knowledge of variables is required
There are independent and dependent variables
Pre-defined groups are compared
No manipulation of variables
No random assignment of individuals or groups
Degree of cause-effect is uncertain.

6. Advantages
Allows cause-effect relationship study when subject manipulation is impossible or very difficult
Allows to study many relationships within a given population at one time.

7. Problems
Degree at which a researcher can determine the causal-effect with any measure of certainty is not known
In relationship study of X and Y, it may reveal X causes Y, Y causes X, or another variable Z cause both X and Y.

8. Similarities between causal-comparative and correlational research
Both seek to explore relationships among variables
Both try to identify variables that are worthy of exploration through experimental research
Neither allow manipulation
Both attempt to explore causation but causation must be argued: no causal statements.

9. Differences between causal-comparative and correlational research
Correlational Resarch
Causal-Comparative Research
Requires a score on each variable for each subject
Studies two or more groups of subjects
Investigates two or more quantitative variables
Involves at least one categorical variable (e.g. gender)
Analyzes data using scatterplots and/or correlation coefficients
Compares averages or uses crossbreak tables

10. Similarities between causal-comparative and experimental research
Both require at least one categorical variable (e.g. gender)
Both compare group performances to determine relationships
Both compare separate groups of subjects .

11. Differences between causal-comparative and experimental research
Causal-Comparative Research
Independent variable is manipulated
No manipulation
Provides stronger evidence for causation
Provides weaker evidence for causation
Researcher has flexibility in forming the structure of design
Groups are already formed

12. Designing Groups Defined Group:
Group must be defined as the one that possesses the characteristic to be studied
Definition must be precise for understanding and interpretation of findings
E.g.
Science literacy study defined one teacher population as being “high context-enriched” in their instruction and the other as “low context-enriched”

13. Comparison Groups
Select group not possessing (or not to the same degree) the defined characteristic
It usually has similar characteristics with exception of the variable that is the focus of the study.

14. A sample for causal-comparative research
Group
Independent Variable
Dependent Variable
(a) I C
Participation
(has the characteristic) O
Level of motivation II -C
Non-participation
(does not have the characteristic)
(b) C1
Counselors
(one characteristic)
Amount of job satisfaction C2
Teachers
(another characteristic)
0 Amount of job satisfaction

15. Strengthening research design
Because the participants are not selected randomly and there is no manipulation, internal validity is threatened.
Thus, one (or two) of the following techniques must be used while forming the groups ( can be selected in the statistics program):
Pair-wise Matching
Extreme groups
Analysis of covariance (ANCOVA)

16. Instrumentation / Data Collection
Different types of instruments can be used in causal- comparative research: achievement tests, questionnaires, observational devices, attitudinal measures, etc.

17. Data Analysis
A variety of descriptive and inferential statistics can be used
Desctiptive statistics
Mean, median, mode
Standard deviation
Inferential statistics
T-test
ANOVA
Chi-square

18. Interpreting the Results
The results must be interpreted with caution.
As with correlational studies, they identify relationships but do not prove cause and effect.
There are two main ways to strengthen the interpretability of such studies:
Formulating alternative hypotheses and investigating them whenever possible
Examining all of the variables if the dependent variable is categorical