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Quasi-experimental designs

Quasi-experimental designs are powerful designs for establishing associations

Quasi-experimental designs are a series of methods that possess the benefits of random selection, but lack the other necessary component needed to make causal inferences in experimental research designs, random assignment. Because randomization both at the population and group level allows for any group differences to be written off to chance at baseline, the lack of random assignment in quasi-experimental designs does not allow you to make causal inferences between variables.

With that being said, quasi-experimental designs are very feasible designs for busy clinicians and applied empiricists. These designs are also useful in research endeavors where random assignment is not ethical and when longitudinal data needs to be collected.

There are many different types of quasi-experimental designs and researchers choose the design that best answers their research question. For practical purposes, Research Engineer will focus on four of the most prevalent quasi-experimental designs. 

Types of quasi-experimental designs

Test multiple interventions simultaneously across several independent groups.
Counterbalanced Design
Test the effects of an intervention with multiple pre-intervention and multiple post-intervention observations of an outcome.
Interrupted Time Series Design
Participants are randomized at the treatment level to either a treatment or control group and the groups are compared on treatment effects.
Nonequivalent Control Group
A longitudinal study with multiple "wash-out" periods where the treatment is given and then taken away.
Equivalent Time Sample Design

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There are four prevalent types of quasi-experimental designs: Counterbalanced, interrupted time series, nonequivalent control group, and equivalent time samples.

Contact Dr. Eric Heidel
consultation@scalelive.com
(865) 742-7731

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