By: Lee Mei Shen (Matric No. P96736)
NNNC 6013 RESEARCH METHODOLOGY & STATISTICS
LECTURER: ASSOCIATE PROFESSOR DR. NORMAH CHE DIN
• Quasi = ‘Resembling’
• A research that resembles experimental research but is not
true experimental research.
• Although the independent variable is manipulated,
participants are not randomly assigned to conditions or
orders of conditions (Cook & Campbell 1979).
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Is random assignment used?
No
Yes
Randomized or
True experiment
Is there a control group or
multiple measures?
Yes
Quasi-experiment
No
Non-experiment
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• Time Series Designs
• Regression-Discontinuity Design
• Non-equivalent Control Group Design
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• A study design in which the control group is not selected
by random means.
• ‘Non-equivalent’ = no random assignment
• Control group is ‘like’ the treatment group.
Chosen from the same population (e.g.: Two comparable
classrooms or two comparable schools)
• 2 types:
Posttest-only non-equivalent control group design
Pretest-posttest non-equivalent control group design
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 More feasible because it often does not have the time and logistical constraints
associated with many true experimental designs.
 More realistic, not all other variables are tightly controlled. → Increased external
validity
 Natural setting → Reactions of test subjects are more likely to be genuine.
 Useful in identifying general trends from the result, especially in social science
disciplines.
 Reduces difficulty and ethical concerns that may surround the pre-selection and
random assignment procedures.
 May reduce the time and resources required because extensive pre-screening and
randomization is not required.
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• This type of study is occasionally called a static group
comparison.
• Compares treatment with no-treatment group.
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• Difference between those who take a
course and those who don’t.
• Comparing two high schools: One with a
pregnancy prevention program and one
without.
• Comparing two classes after they were
taught with 2 different teaching
methods.
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 Problem: Assignment Bias
 Any prior differences between the groups may affect the outcome of
the study.
 E.g. A research study compares test results from students at two
different schools. Even if the researcher controls the age, gender and
grade level of the students being studied, they might not be able to
control factors such as the ethnic background, school quality, family
background, etc. of the students.
 This lack of control can adversely affect the reliability and internal
validity of the experiment.
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• A much stronger version of the nonequivalent control group design is often called a
pretest– posttest nonequivalent control group design and can be represented as follows:
• Use existing groups, which are not randomly assigned to conditions.
• Collect pretest data on both groups.
• Apply the independent variable to one group (control group) but not the other.
• Collect posttest data on both groups.
• The addition of the pretest measurement allows researchers to address the problem of
assignment bias that exists with all nonequivalent group research.
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Non-Random
Assignment
Dependent
Variable
Independent
Variable
Measure
Experimental
group
Dependent
Variable
Measure
Participants
Measure
Control
group
Measure
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• Evaluation of the Peer Tutoring Method
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• Address temporal ordering and empirical
correlation but not internal validity.
• Although the addition of a pretest to the
nonequivalent control group design reduces some
threats to internal validity, it does not eliminate them
completely.
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Possible threats:
• Selection-maturation threat: The two groups are maturing
at different rates.
• Selection-history threat: Participants in one group
experience outside events that the other group does not.
• Statistical regression to the mean: Happens when
unusually large or small measurements tend to be followed
by measurements that are closer to the mean.
• Contamination effects: The treatment and control groups
influence each other in some way.
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 We cannot completely rule out the threat, but it can be
minimized.
 By taking steps to ensure that the two groups are as similar
as possible.
 Increase the internal validity and eliminate some
confounding variables.
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 Quasi-experiment – No random assignment.
 Non-Equivalent Control Group - The control group is not selected by
random means.
 Benefits: Feasible, realistic, increased external validity, save time and
resources etc.
• Two types: Posttest-only non-equivalent control group design and
Pretest-posttest non-equivalent control group design
• Threat to Internal validity
• Widely used to evaluate efficacy of a program or measure in a natural
setting, especially in clinical and educational setting.
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Bordens, K.S. & Abbott, B. B. 2008. Research Design and Methods: A Process Approach. 7th
Ed. New York: McGraw-Hill.
Cook T.D. & Campbell D.T. 1979. Quasi-Experimentation: Design and Analysis Issues for
Field Settings. Dallas: Houghton Mifflin.
Cozby, P.C. & Bates, S.C. 2015. Methods in Behavioral Research. 12th Ed. New York:
McGraw-Hill Education.
Dattalo, P. 2009. Strategies to Approximate Random Sampling and Assignment. New York:
Oxford University Press.
Fife-Schaw, C. 2012. Quasi-experimental designs. In Breakwell, G.M., Smith, J.A. &
Wright, D.B. (ed.). Research Methods in Psychology, pp. 75-92. London: Sage
Publication Ltd.
Iman, J.N. 2017. Debate instruction in EFL classroom: Impacts on the critical thinking and
speaking skill. International Journal of Instruction, 10(4), 87-108.
Shim, M., Lee, Y., Oh, H. & Kim, J. 2007. Effects of a back-pain-reducing program
during pregnancy for Korean women: A non-equivalent control-group
pretest- posttest study. International Journal of Nursing Studies, 44(1),19-28.
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 Q: Can causal relationship be inferred between variables using an quasi-
experimental research?
 A: Quasi-experimental design may not be suitable for research that is intended to
establish causal relationship between variables for several reasons. Unlike true
experimental design, quasi-experimental design does not control for extraneous
variables, posing a great threat to the ability to infer cause-effect relationships from
the variables. The lack of random assignment of participants to experimental and
control poses another threat since, without random assignment, the differential
outcomes could be due to differences between participants in the conditions. As
such, quasi-experimental design may be more suitable to be used to examine a
general trend or to look at the association between two variables, etc.
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