| Literature DB >> 28365306 |
Till Bärnighausen1, Catherine Oldenburg2, Peter Tugwell3, Christian Bommer4, Cara Ebert4, Mauricio Barreto5, Eric Djimeu6, Noah Haber7, Hugh Waddington6, Peter Rockers8, Barbara Sianesi9, Jacob Bor10, Günther Fink7, Jeffrey Valentine11, Jeffrey Tanner12, Tom Stanley13, Eduardo Sierra14, Eric Tchetgen Tchetgen7, Rifat Atun7, Sebastian Vollmer4.
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.Entities:
Mesh:
Year: 2017 PMID: 28365306 DOI: 10.1016/j.jclinepi.2017.02.017
Source DB: PubMed Journal: J Clin Epidemiol ISSN: 0895-4356 Impact factor: 7.407