A quasi-experiment is a research design used to estimate the causal impact of an intervention. Quasi-experiments share similarities with experiments and randomized controlled trials, but specifically lack random assignment to treatment or control. Instead, quasi-experimental designs typically compare groups that are either preexisting (e.g., different dog breeds) or groups that were created without random assignment (e.g., students attending different universities).
A quasi-experiment is a research design used to estimate the causal impact of an intervention. Quasi-experiments share similarities with experiments and randomized controlled trials, but specifically lack random assignment to treatment or control. Instead, quasi-experimental designs typically compare groups that are either preexisting (e.g., different dog breeds) or groups that were created without random assignment (e.g., students attending different universities).
The causal analysis of quasi-experiments depends on assumptions that render non-randomness irrelevant (e.g., the parallel trends assumption for DiD), and thus it is subject to concerns regarding internal validity if the treatment and control groups are not comparable at baseline. In other words, it may be difficult to convincingly demonstrate a causal link between the treatment condition and observed outcomes in quasi-experimental designs. This is particularly true if there are confounding variables that cannot be controlled or accounted for.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).