Causal-comparative research attempts to identify potential cause-and-effect relationships by comparing two or more groups that differ on some independent variable. Researchers select naturally occurring groups that vary on the independent variable, rather than manipulating the variable through experimentation. There are three types: exploration of effects, causes, and consequences. Threats to internal validity include lack of randomization and control. Analysis involves comparing means and frequencies between groups using t-tests, ANCOVA, or other inferential statistics.

1. CAUSAL COMPARATIVE
RESEARCH

2. CAUSAL COMPARATIVE
RESEARCH

3. What is Causal-Comparative
Research?
 In this type of research investigators
attempt to determine the cause or
consequences of differences that already
exist between or among groups of
individual.
 Also known as “ex post facto” research

4. TYPES of Causal-Comparative
Research
There are three types of causal comparative
research:
 Exploration of effects
 Exploration of causes
 Exploration of consequences

5. EXAMPLES
 How does pre-school attendance affect
social maturity at the end of the first grade?
 How does having a working mother affect a
child’s school absenteeism?

6. DESIGN OF CAUSAL-
COMPARATIVE RESEARCH

7.  The researcher selects two groups of
participants, the experimental and control
groups, but more accurately referred to as
comparison groups.
 Groups may differ in two ways.
One group possesses a characteristic that the
other does not.
Each group has the characteristic, but to differing
degrees or amounts.

8. Types Researchof Causal-Comparative
Designs
There are two types of causal-
comparative research designs:
 Retrospective causal-comparative research
 Prospective causal-comparative
research.

9. Retrospective causal-comparative
research
Retrospective causal-comparative
research
begins
requires that
investigating
a researcher
a particular
question when the effects have already
occurred and the researcher attempts to
determine whether one variable may
have influenced another variable.

10. Prospective causal-comparative
research
Prospective causal-comparativess research
occurs when a researcher initiates a study beginning
with the causes and is determined to investigate the
effects of a condition. By far, retrosspective causal-
comparative research designs are much more common
than prospective causal-comparative designs (Gay et
al., 2006).

12. The researcher observe that 2 groups
differ on some variable (teaching style)
and then attempt to find the reason for
(or the results of) this difference.
***Note that the difference has
already occurred.***

13.  Causal-comparative studies attempt to
identify cause-effect relationships.
 Causal-comparative studies typically
involve two (or more) groups and one
independent variable.
 Causal-comparative studies involve
comparison.

14.  The basic causal-comparative approach
involves starting with an effect and seeking
possible causes (retrospective).
 The basic approach starts with cause and
investigates its effects on some variable
(prospective).
 Retrospective causal-comparative studies
are far more common in educational
research.

15. Steps for Conducting a Causal-
Comparative Study
The following steps, as
described by Lodico et al.
(2006), should be adhered
to by researchers
conducting a causal-
comparative study.

16. Step One: Select a Topic
Topics studied with
causal- comparative
research designs
typically catch a
researcher’s
attention based on
experiences or situations

17. Step Two: Review of literature
Reviewing published literature
on a specific topic of interest is
especially important when
conducting causal- comparative
research as such a review can
assist a researcher in
determining which extraneous
variables may exist in the

18. Step Three: Develop a Research
Hypothesis
Hypotheses developed for causal-
comparative research to identify the
independent and dependent variables.
Causal-comparative research hypotheses
should describe the expected impact of
the independent variable on the
dependent variable.

19. Step Four: Select Participants
In causal-comparative research participants
are already organized in groups. The
researcher selects two groups of participants,
the experimental and control groups, but more
accurately referred to as comparison groups
because one group does not possess a
characteristic or experience possessed by the
second group or the two groups differ in the
amount of a characteristic that they share.The
independent variable differentiating the groups
must be clearly and operationally defined,
since each group represents a different

20. Step Five: Select Instruments to
Measure Variables & Collecting
Data
As with all of types of quantitative research,
causal-comparative research requires that
researcher select instruments that are reliable
and allow researchers to draw valid
conclusions (link to reliability and validity
portion of site). After a researcher has selected
a reliable and valid instrument, data for the
study can be collected.

21. Step Six: Analyze and Interpret
Results
Typically, in causal-comparative studies data is
reported as a mean or frequency for each group.
Inferential statistics are then used to determine
whether the means “for the groups are
significantly different from each other” (Lodico et
al., 2006, p. 214). Since casual-comparative
research cannot definitively determine that one
variable has caused something to occur,
researchers should instead report the findings of
causal comparative studies as a possible effect or
possible cause of an occurrence.

22. Threats to Internal Validity inCausal-Comparative Research
 The possibility exists that the groups are not
equivalent on one or more important variables
 Lack of randomization
 Inability to manipulate an independent variable
 Data collector bias
 History
 Maturation

23.  Oftentimes subject bias occurs
 Instrument decay
 Attitude
 Regression
 Pre-test/treatment interaction effect
 Loss of subjects
 Location

24. Data Analysis
 In a Causal-Comparative Study, the first step
is to construct frequency polygons.
 Means and SD are usually calculated if the
variables involved are quantitative.
 The most commonly used inference test is a t-
test for differences between means.
 ANCOVAs are useful for these types of
studies.

25. ANALYSIS OF COVARIANCE
 I
 It is used to adjust initial group differences on
variables used in causal-comparative and
experimental research studies.
 Analysis of covariance adjusts scores on a
dependent variable for initial differences on some
other variable related to performance on the
dependent.
 Suppose we were doing a study to compare two
methods, X and Y,of teaching fifth graders to
solve math problems.
 Covariate analysis statistically adjusts the scores
of method Y to remove the initial advantage so
that the results at the end of the study can be

26.  Analysis of data also involves a variety of
descriptive and inferential statistics.
 The most commonly used descriptive
statistics are
(a) The Mean, which indicates the average
performance of a group on some measure
of a variable, and
(b)The Standard Deviation, which indicates
how spread out a set of scores is around
the mean, that is, whether the scores are
relatively homogeneous or heterogeneous
around the mean.

27.  The most commonly used inferential
statistics are:
 (a) The t test, used to determine whether
the means of two groups are statistically
different from one another;
 (b) Analysis of variance, used to
determine if there is significant difference
among the means of three or more groups;
and
 (c) chi square, used to compare group
frequencies, or to see if an event occurs

28. Limitations of Use:
 There must be a “pre-existing” independent
variable
 Years of study, gender, age, etc.
 There must be active variables- variables which the
research can manipulate
 The length and number of
study sessions, instructional
techniques, etc.
 Lack of randomization, manipulation, and control
factors make it difficult to establish cause-effect