The Nuts and Bolts of Quasi-experiments
McBride Ch. 12
Quasi-Experiments
A type of research design
where a comparison is made, as in an experiment, but no random
assignment of participants to groups
occurs.
Quasi-independent/subject variable: variable that allows
comparison of groups of participants without manipulation
(i.e., no random assignment).
Many applied studies that examine realistic behaviors make use
of quasi-experiments because random assignment would be
difficult or impossible or unethical.
For example, research done in educational settings often
involves a quasi-experiment, because the researcher cannot
affect the classroom students are in or the teacher they have.
Thus, different classes of students may be compared on a
behavior of interest, but the researcher will not gain strong
causal evidence because of the lack of random assignment.
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Pretest-Posttest Designs
A behavior is measured
twice: once before a treatment or condition is implemented (the
pretest) and once after it has
been implemented (the posttest).
This design is a
quasi-experiment because there is no random assignment of
participants to the treatment. In this case, all the
participants get the treatment. The researcher compares the
scores from the pretest
and the posttest, looking for a change based on the treatment or
condition occurring between the two measurements.
Researchers can attempt to
deal with some of the alternative explanations in
pretest-posttest
designs by including a
control group.
If participants are randomly assigned to the control group and
the treatment group, the study becomes an experiment. However,
in many situations random assignment to groups may not be
possible. Without random assignment, the study is still a
quasi-experiment, where it is difficult to rule out alternative
explanations of the results.
This design is a pretest-posttest design with nonequivalent
groups, because group differences that might account for the
results are not controlled by random assignment to groups.
Sources of Bias
History effects--events
that occur during the course of a study to all or individual
participants that can result in bias.
Example:
A study was reported in the
media during the time between measurements of smoking cessation
that concluded that smoking has extremely harmful effects.
Testing effects--occur
when participants are tested multiple times and each subsequent
test is affected by the previous tests.
Example: participants may get better on the tests over time with
practice. Alternatively, they may become fatigued or bored with
the test after taking it once.
Regression toward the mean--can
occur when participants score higher or lower than their
personal average—the next time they are tested, they are more
likely to score near their personal average, making scores
unreliable.
Example: A high score achieved at
posttest may be an extreme score in some cases, and with
additional testing, these students may score closer to their
original mean (which is typically lower than the norm).
Maturation--natural
changes that occur to the
participants during the course of a study that can result in
bias.
Example:
this
can include actual
maturation, as in developmental studies where
individuals are observed at different ages, or
other types of changes that occur to individuals
over a period of time.
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Attrition--occurs
when participants choose
not to complete a study.
Example:
in
the depression treatment
study, suppose that some of the participants in
the study drop out during the 12-week period and
do not return for the posttest.
It is possible that these participants who have
chosen not to complete the study did so because
they have worse depression symptoms than the
participants that remained in the study.
Questions to think about:
a) What aspects of a study allow tests of causal
relationships?
b) Describe three main sources of bias that can affect the
results of a quasi-experiment.