Comparing True Experiments to Quasi-experiments
Kristen Tolman
Department of Behavioral Sciences, Utah Valley University
BESC 3020 X02: Research Methods for the Behavioral Sciences
Dr. Robert Line
Jun 19, 2021
Comparing True Experiments to Quasi-experiments
An experiment is a type of study to conclude a hypothesis using variables to measure, compare
and calculate and variables that can be manipulated. Variables are values or characteristics the
researchers aim to measure in a study, such as complex phenomena or numerical data. The
independent variables are stable as their value is independent of other variables in the study. The
dependent variable is the effect, as the value depends on the changes in the independent variable.
(Privitera, Gregory) In other words, the independent variable is manipulated or changed by the
experimenter to measure the effect of this change on the dependent variable.
Experimental design means creating a set of procedures, usually dividing participants into two
groups, a control group, and an experimental group. Qualitative research is often divided into
either experimental or quasi-experimental research. There are three significant types of
experimental design; true experiments and quasi-experiments, and nonexperimental. (Privitera,
Gregory) These types of experimental designs are used to discover the causal relationship
between independent and dependent variables.
In a true experiment, the researcher will randomly assign subjects or participants to different
groups or conditions. Random assignment produces greater validity of an experiment, which
means that the experiment validates if the experiment is trustworthy. Two types of validity in
experiments are internal and external. (Price)
For the researchers to have internal validity, researchers must have well-constructed
experimental designs. Internal validity is essential because it ascertains how well the experiment
determines the claim of the cause and effect of the study. In this type of design, the independent
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Comparing True Experiments to Quasi-experiments
and dependent variables, pre-testing and post-testing, and experimental and control groups are
entirely controlled and adequately checked.
Threats to internal validity are often the elements or details of the study, referred to as
environmental factors. These factors include the time, setting, testing, instrumentation, and
treatment of the participants. (Privitera, Gregory) An example of the instrumentation use
affecting the experiment would be if the instruments used during the study were altered in any
way, affecting the internal validity, opening different possible explanations for the outcome.
Contrastingly, external validity is related to the validity of factors outside the study and the
constraints involved. External validity assists in concluding the study conducted to support
generalizing the results to a greater population- outside of those studied. Generally, studies are
considered high in external validity when the participants and the circumstances are consistent
with those that the researchers want to postulate and create a situation that appears and feels
more "real" or a situation that the participants would regularly experience; referred to as
mundane realism.
Amidst crucial components that may disturb external validity include experimental
arrangements, the population the sample is drawn from, and the interplay of the experimental
treatment of selection bias. (Campbell & Stanley) An example of an experiment conducted in
1997 with low external validity is "That swimsuit becomes you: sex differences in selfobjectification, restrained eating, and math performance." In this study, Fredrickson asked
college students to complete a math test while wearing a swimsuit. This issue lowered the
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Comparing True Experiments to Quasi-experiments
external validity because it is out of the ordinary to wear a swimsuit while taking a math test.
(Fredrickson)
Compared to a true experiment, a quasi-experiment assigns participants or subjects to groups
derived on non-random or organized criteria; in other words, they are not randomly assigned.
Quasi-experiments have lower internal validity than true experiments because the treatment and
control groups may not be measurable at the beginning. This issue makes it more challenging to
determine a causal relationship between the treatment and the results. (Rossi) There are
situations where quasi-experimental designs are more appropriate or useful than true
experimental designs, such as when it would be unethical to use a true experiment. Moreover, it
may be impractical or impossible to control the critical factors in a true experiment. (Privitera,
Gregory)
The most commonly used quasi-experiment is the nonequivalent group design. In a true
experiment, the treatment and control groups are viewed as equivalent in all respects other than
treatment. However, in a quasi-experiment, they differ in other ways as well and have not been
randomly assigned conditions; thus, they are nonequivalent. Additionally, these groups appear
to be similar, but only one of the groups receives treatment. (Cook)
Both types of design require a post-test and pretest and have two-group designs. In post-test only
nonequivalent group design, one group receives treatment and is compared to the nonequivalent
group or participants not exposed to treatment. (Privitera, Gregory) An example would be a
researcher attempting to evaluate whether or not participants with ADHD improved while treated
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Comparing True Experiments to Quasi-experiments
with medication, then compare them to a group given placebo or sugar pills. Researchers would
compare and measure the levels of anxiety between the groups. This design would be a
nonequivalent group design because the persons in each group are assigned the medication by
the researcher, possibly explaining crucial differences between the two groups. (Price)
One way to improve the post-text-only group design would be to create a pretest-posttest
nonequivalent group design. In this design, one group would be given a pretest before receiving
treatment, then given a post-test after receiving treatment. While at the same time, a
nonequivalent control group is also given a pre-test but does not receive treatment and then given
a post-test. (Privitera, Gregory) This method compares whether or not the treated group
improved and if their improvement is more significant than those who did not receive treatment.
(Morgan)
In conclusion, experimental designs help confirm the hypothesis. It has been established that
both true and quasi-experimental work in different settings and situations. The chief hindrance to
a true experimental design is that it can be challenging to carry out in a "real world" situation. In
contrast, quasi-experimental design is much easier to accomplish. However, quasi-experimental
internal results are not quite as valid. Additionally, it has been revealed that it is nearly
unachievable to attain high degrees of internal and external validity. For example, rigid controls
for internal validity cause challenges in practically generalizing the results. Diversely,
experiments with high levels of external validity demonstrate weak internal validity.
Nevertheless, the random selection of participants or subjects and random assignment to variable
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Comparing True Experiments to Quasi-experiments
treatments can assist in managing a more significant number of threats to internal and external
validity. (Cozby)
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Comparing True Experiments to Quasi-experiments
References
Cambell, D. T., & Standley, J. C. (n.d.). Experimental and Quasi-experimental Designs for
Research [PDF]. Houghton Mifflin Company.
Cozby, P. C., & Bates, S. C. (2012). Methods in Behavioral Research. Retrieved June 19,
2021.
Morgan, G. A. (2000). Quasi-Experimental Designs. Journal of the American Academy of
Child & Adolescent Psychiatry. Retrieved June 19, 2021.
Price, P. Jhangiani, R. S., Cutler, C., Leighton, D., Metz, M. A., & Chiang, I. C. (n.d.).
Research Methods of Psychology – 2nd Canadian Edition. [Ebook]. Retrieved June 19,
2021, from https://opentextbc.ca/researchmethods/
Rossi, P. H., Lipsey, M. W., & Freeman, H. E. (2004). Evaluation: A systematic approach.
Thousand Oaks, CA: Sage.
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