Quasi-experimental study designs series-paper 7: assessing the assumptions

J Clin Epidemiol. 2017 Sep;89:53-66. doi: 10.1016/j.jclinepi.2017.02.017. Epub 2017 Mar 29.

Abstract

Quasi-experimental designs are gaining popularity in epidemiology and health systems research-in particular for the evaluation of health care practice, programs, and policy-because they allow strong causal inferences without randomized controlled experiments. We describe the concepts underlying five important quasi-experimental designs: Instrumental Variables, Regression Discontinuity, Interrupted Time Series, Fixed Effects, and Difference-in-Differences designs. We illustrate each of the designs with an example from health research. We then describe the assumptions required for each of the designs to ensure valid causal inference and discuss the tests available to examine the assumptions.

MeSH terms

  • Humans
  • Non-Randomized Controlled Trials as Topic / methods*
  • Non-Randomized Controlled Trials as Topic / statistics & numerical data*
  • Research Design / statistics & numerical data