Quasi-Experimental Designs: Definition, Characteristics, Types & Examples

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  • 0:05 Definition
  • 2:06 Non-Equivalent Groups
  • 3:29 Pretest-Posttest
  • 5:21 Cross Sectional and…
  • 6:53 Ex Post Facto
  • 7:52 Lesson Summary
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Lesson Transcript
Instructor: Devin Kowalczyk

Devin has taught psychology and has a master's degree in clinical forensic psychology. He is working on his PhD.

This lesson explores the basic definition of why there is the label of quasi-experimental design in addition to what types of designs are quasi-experimental.

Quasi-Experiment: Definitions

I'm going to do a psychological experiment where I make people different ages and then see how they react to loud noises. Well, I'd like to. Unfortunately, even with our advanced quantum physics and computers, we cannot reverse or control age like that. Psychological researchers are forced to work around the issue.

Because we can't reverse someone's age, we have to work with people who are already that age. But, we miss some things in the process. But, I'm getting ahead of myself.

A true experiment has one main component - randomly assigned groups. This translates to every participant having an equal chance of being in the experimental group, where they are subject to a manipulation, or the control group, where they are not manipulated.

A quasi-experiment is simply defined as not a true experiment. Since the main component of a true experiment is randomly assigned groups, this means a quasi-experiment does not have randomly assigned groups. Why are randomly assigned groups so important since they are the only difference between quasi-experimental and true experimental?

When performing an experiment, a researcher is attempting to demonstrate that variable A influences or causes variable B to do something. They want to demonstrate cause and effect. Random assignment helps ensure that there is no pre-existing condition that will influence the variables and mess up the results.

A silly example would be something like, 'Does chemical X1 cause blindness?' If you accidentally put all of the people wearing glasses in the condition where you spray X1 in someone's face, then your results are going to be skewed. This is an extreme and overly simplistic example, but it is demonstrating why normally an experimenter wants to randomly assign people into different groups. Let's look at some more realistic and typical quasi-experiments in psychology.

Non-Equivalent Groups

Sometimes a researcher needs a particular type of participant or they only have access to a certain group of participants. This means that the researcher collects participants in a group that cannot or should not be divided up, or more simply, the researcher cannot randomly assign the participants. This non-equivalent group is defined as an experiment where existing groups are not divided.

An experiment using non-equivalent groups might take place at a mental health institution. You cannot randomly assign people to therapy and others to not have therapy. That would be unethical. So, you're forced to assign the entire group to therapy, which means no random assignment.

It is possible to have multiple groups. In our mental health institution example, let's say that the staff had divided up everyone into three groups. Furthermore, let's say you have a new type of therapy and an old type of therapy, so nobody is going without.

Randomly assigning the groups, to try and make your study a true experiment, is not sufficient. This is because there is no telling why an individual was assigned to any of the three groups. The reason an individual might be in group B and not in group A could skew your results. You need to be able to assign individuals to the treatment or alternate treatment groups to claim it as a true experiment.


A researcher finds a group of people to test. Then the researcher introduces a manipulation that should change the people and test to see if there were any changes. For example, you test a group of people on their knowledge of U.S. history. Then you assign them a study packet and test them again to see if their knowledge has increased. This is known as a pretest-posttest design, which is when participants are studied before and after the experimental manipulation.

A researcher can use pretest-posttest in an almost unlimited number of ways, as long as they follow the steps:

  • Test the participants prior to the experimental manipulation.
  • Perform the experimental manipulation, which is a fancy way of saying that you would do something to the group, like give them homework or give them therapy or deafen them with noise.
  • Test the participants after the manipulation to see what changes occurred.

The reason pretest-posttest is considered a quasi-experimental design is because the majority of researchers will manipulate their entire group. This gives them a larger sample size to see if their manipulation actually changed the group. It is possible to randomly assign people to the experimental or control condition to make it a true experiment, but you're reducing your sample size, and this could put a strain on your statistics.

Another example of a pretest-posttest design might be examining the effects of not sleeping. You take participants and test them to see how good their judgment is, their knowledge and their hand-eye coordination. Then you keep them up all night with cola, games and bright lights. Keeping them up is your experimental manipulation. Lastly, you test them in the morning to see what effect the lack of sleep had on their judgment, knowledge and hand-eye coordination.

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