What is Causal-Comparative
In this type of research investigators
attempt to determine the cause or
consequences of differences that already
exist between or among groups of
Also known as “ex post facto” research
TYPES of Causal-Comparative
There are three types of causal comparative
Exploration of effects
Exploration of causes
Exploration of consequences
Attempts to identify cause and effect relationships.
Involve two or more group variables.
Involve making comparison.
Individuals are not randomly selected and assigned to two or
Cannot manipulate the independent variables.
Less costly and time consuming.
How does pre-school attendance affect
social maturity at the end of the first
How does having a working mother affect
a child’s school absenteeism?
-The researcher selects two groups of
participants, the experimental and control
groups, but more accurately referred to as
-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.
Types of Causal-Comparative Research
There are two types of causal-
comparative research designs:
research requires that a researcher
begins investigating a particular
question when the effects have already
occurred and the researcher attempts to
determine whether one variable may
have influenced another variable.
Prospective causal-comparative research
occurs when a researcher initiates a study
beginning with the causes and is determined
to investigate the effects of a condition. By
far, retrospective causal-comparative research
designs are much more common than
prospective causal-comparative designs (Gay
et al., 2006).
Basic approach of causal-
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
Causal-comparative studies attempt to
identify cause-effect relationships.
Causal-comparative studies typically
involve two (or more) groups and one
Causal-comparative studies involve
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
Retrospective causal-comparative studies
are far more common in educational
Steps for Conducting a Causal-
The following steps, as described by
Lodico et al. (2006), should be
adhered to by researchers
conducting a causal-comparative
Step One: Select a Topic
Topics studied with causal-
comparative research designs
typically catch a researcher’s
attention based on experiences or
situations that have occurred in the
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 situation that they are considering
Step Three: Develop a Research
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
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
Step Five: Select Instruments to
Measure Variables & Collecting
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.
Step Six: Analyze and Interpret
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.
Threats to Internal Validity in
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
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
ANALYSIS OF COVARIANCE
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
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
Analysis of data also involves a variety of
descriptive and inferential statistics.
The most commonly used descriptive
(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.
The most commonly used inferential
(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;
(c) chi square, used to compare group
frequencies, or to see if an event occurs
Limitations of Use:
There must be a “pre-existing” independent
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 relationships with any degree of