**Causal-Comparative Research**

Causal-comparative
educational research attempts to identify a causative relationship between an
independent variable and a dependent variable. However, this relationship is
more suggestive than proven as the researcher does not have complete control
over the independent variable. If the researcher had control over the
independent variable, then the research would be classified as true
experimental research.

There
are many occasions while conducting educational research during which the
researcher is unable to control the independent variable, or it would be
unethical to control the independent variable, or it is simply too difficult to
control the independent variable. For example, someone attempting to find the
effect of gender (male or female) on an educational dependent variable would
not be able to experimentally manipulate gender, and thus would use a
causal-comparative research design rather than an experimental design for the
research.

The
statement or title of a causal-comparative research study takes the form: The
effect of [independent variable] on [dependent variable] for [subjects], with
the understanding that the independent variable is not under experimental
control.

An
example would be "The effect of gender on a visual alertness measure for
6th grade public school pupils." Here the independent variable is gender
and the dependent variable is the visual alertness task.

Another
example of a causal-comparative research design would be "Classroom
behavior of good and poor readers." In this study the independent variable
would be good readers versus poor readers. The researchers identified the three
students with the highest scores and three students with the lowest scores on a
reading achievement test for each of 18 classrooms. The dependent variable,
classroom behavior, was measured by having a trained observer, measure the
frequency of seven classroom behaviors during a 30 minute period of time over
ten days. The observer did not know which of the pupils she was observing were
good readers and which were poor readers. The complete reference for this study
is:

Wasson,
B., Beare, P., and Wasson, J. B. (1990). Classroom behavior of good and poor
readers.

*Journal of Educational Research, 83,*162-165.
"An
important difference between causal-comparative and correlational research is
that causal-comparative studies involve two or more

**groups**and one independent variable, while correlational studies involve two or more**variables**and one group." (Gay & Airasian, 2000, 364).**Causal-Comparative Research Designs**

The
basic design of a causal-comparative research study is to select a group that
has the independent variable (the experimental group) and then select another
group of subjects that does not have the independent variable (the control or
comparison group). The two groups are then compared on the dependent variable.
For example, in your junior high school, some of the seventh grade math classes
use hand held calculators in their seventh grade mathematics classes, while
other classes do not use calculators. You want to find the effect of calculator
use on mathematics grades at the end of the year. So you select a group of
students from the classes that use calculators and then select another group of
the same size from the classes that do not use calculators and compare the two
groups at the end of the year on their final math grades. Another variant of
this study would be to take the students from one class that uses calculators
and compare them with another class that does not use calculators. Both these
studies would be causal-comparative research studies but they would differ in
how you can generalize the results of your study. The results of the first
study could be generalized to the seventh grade students taking mathematics classes
in your school while the second study could only be generalized to the two
classes that participated in the study.

Instead
of using an experimental group and a control group as in the study considered
above, you could have a causal-comparative research study in which two or more
groups differ in some variable that constitutes the independent variable for
the study. For example a study might wish to compare students at four different
age levels (or grade levels) on their amount of participation in extra-curricular
activities. The researcher could look at the number of extra-curricular
activities participated in by four groups of students. The first group would be
students in grades 1-3, the second group students in grades 4-6, the third
group students in grades 7-9, and the fourth group students in grades 10-12.
The independent variable in this study would be grade placement and the
dependent variable would be participation in extra-curricular activities (the
effect of grade level on participation in extra-curricular activities for
public school students grades 1-12).

One
of the problems with causal-comparative research is that since the pupils are
not randomly placed in the groups, the groups can differ on other variables
that may have an effect on the dependent variable. In experimental research we
can assume that these other variables cancel out among the study groups by the
process of randomization. However, in causal-comparative research if we are
suspicious that some external variable might be involved, we can use some
control procedure in an attempt to ameliorate the effect of the external
variable.

**Control Procedures for Causal-Comparative Studies**

**Matching**is one way to help control the effect of extraneous variables on the dependent variable in a causal-comparative study. For example, let's say you do not think that the two groups that you are using to evaluate a new approach to reading instruction are similar on verbal ability. Further you suspect that verbal ability might be related to the dependent variable in this study. The dependent variable is performance on a reading test. To overcome this difficulty you assess each of your students with a measure of verbal ability, such as a test of general intelligence, and then select pairs of subjects, one from each group, that are similar to each other in verbal ability.

In
this causal-comparative study, the independent variable is method for reading
instruction. The dependent variable is reading proficiency, and verbal ability
is the matching or control variable.

Another
method to control the effect of an extraneous variable on the dependent
variable is to

**compare homogeneous subgroups**. We could do this in the previously mentioned study by restricting our subject selection from each of the groups, to those with tested IQ's in the range 90-110. This would constrict the number of subjects we could use in our study, but would help control the effect of tested intelligence (verbal ability) on the dependent variable in the study.
A
third method that is sometimes used to control the effects of an extraneous
variable is

**analysis of covariance**. Analysis of covariance is a statistical method of control in which the scores on the dependent variable are adjusted for the subject's initial differences in the control variable.**Data Analysis for Causal-Comparative Studies**

An
inferential statistic used in both causal-comparative and experimental research
designs is the t-test. Where the subjects in the two groups are independent of
one another, that is no matching of subjects or other control procedures were
used, the

**independent t-test**is used to test the significance of a difference between the means of the experimental and control groups in the study. In research designs where the influence of an extraneous variable has been controlled, or in designs utilizing a pre-test-post-test procedure, the appropriate t-test to use to compare the two groups would be the**dependent t-test**
When
you have three or more groups to compare, the appropriate inferential statistic
to use would be

**one-way analysis of variance**. This statistic shows the significance of differences in the means of three or more groups of subjects.
In
cases where you are using frequency counts for the dependent variable, the
appropriate inferential statistic to use would be the

**chi-square**test. This statistic tests the significance of differences between two or more groups (independent variable) in frequencies for the dependent variable. For example, a high school social studies teacher wants to see if the major party political affiliation for students is similar to or different than that of the registered voters in the county where his high school is located. The teacher would ask the students (anonymously) to indicate whether they would support the Democratic Party or the Republican Party. The proportion of students selecting the democratic or republican parties would be compared with the county proportions of democratic and republican voters using the chi-square statistic.
Read
a causal-comparative research study, preferably one you identified in your
review of the related literature, and state the following components for the
study you read.

- Indicate the problem for the study
- Describe the subjects for the study.
- Describe the instruments used in the study.
- Describe the design of the study
- Describe the procedures (how was the study conducted).
- Describe how the data for the study was analyzed.
- List the major conclusions of the study.

You
should include the following items or components about the study you read:

- Complete APA style reference for the article
- The problem
- The subjects
- The instruments
- The design of the study
- The procedures
- The method of data analysis
- The major conclusions