Quasi-experiment

A quasi-experiment is a <a href="/facts/Research_design/hjmH1Yv5">research design</a> used to estimate the <a href="/facts/Causal/Swh496X7">causal</a> impact of an intervention. Quasi-experiments share similarities with <a href="/facts/Experiment/esltM54f">experiments</a> and <a href="/facts/Randomized_controlled_trial/LG9lkyVx">randomized controlled trials</a>, but specifically lack <a href="/facts/Random_assignment/TDeSKXtu">random assignment</a> to treatment or control. Instead, quasi-experimental designs typically allow assignment to treatment condition to proceed how it would in the absence of an experiment.
Quasi-experiments are subject to concerns regarding <a href="/facts/Internal_validity/mfyCA0n1">internal validity</a>, because the treatment and control groups may not be comparable at baseline. In other words, it may not be possible to convincingly demonstrate a causal link between the treatment condition and observed outcomes. This is particularly true if there are <a href="/facts/Confounding_variables/G4TVx1dt">confounding variables</a> that cannot be controlled or accounted for.
With random assignment, study participants have the same chance of being assigned to the intervention group or the comparison group. As a result, differences between groups on both observed and unobserved characteristics would be due to chance, rather than to a systematic factor related to treatment (e.g., illness severity). Randomization itself does not guarantee that groups will be equivalent at baseline. Any change in characteristics post-intervention is likely attributable to the intervention.

Quasi-experiment open-in-new

Quasi-experiment