Quasi-experimental design

ABSTRACT

Quasi-experiments are similar to randomized controlled trials in many respects, but there are many challenges in designing and conducting a quasi-experiment when internal validity threats are introduced from the absence of randomization. This paper outlines design, measurement and statistical issues that must be considered prior to the conduct of a quasi-experimental evaluation. We discuss challenges for the internal validity of quasi-experimental designs, inclusion/exclusion criteria, treatment and comparator cohort definitions, and the five types of explanatory variables that one must classify prior to analysis. We discuss data collection and confidentiality, statistical power and conclude with analytic issues that one must consider.

KEYWORDS:

• Quasi-experimental design
• retrospective analysis
• observational study design
• cohort

Acknowledgments

Dr Maciejewski received support from VA HSR&D for Research Career Scientist award (RCS 10–391) and owns Amgen stock due to his spouse's employment.

Disclosure statement

No potential conflict of interest was reported by the author.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

VA HSR&D for Research [grant number RCS 10-391] and HSR&D funding for SDR [grant number SDR 13-426].

Notes on contributors

Matthew L. Maciejewski

Matthew L. Maciejewski is a research career scientist in the Durham VA HSR&D Center of Innovation and professor in the Department of Population Health Sciences at Duke University.