Quasi-experimental study designs series – Paper 10: Synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges

Becker, Betsy Jane, Aloe, Ariel M., Duvendack, Maren ORCID: https://orcid.org/0000-0002-8125-9115, Stanley, T.D., Valentine, Jeffrey C., Fretheim, Atle and Tugwell, Peter (2017) Quasi-experimental study designs series – Paper 10: Synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges. Journal of Clinical Epidemiology, 89. pp. 84-91. ISSN 0895-4356

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Abstract

Objective: To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs), and to provide a statistical model for use in analysis. Study Design and Setting: We drew on the literatures of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of quasi-experiments, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed. Results: Biases, confounding, design complexities and comparisons across designs offer serious challenges to syntheses of QEs. Key components of meta-analyses of QEs were identified, including the aspects of QE study design to be coded and analyzed. Of utmost importance are the design and statistical controls implemented in the QEs. Such controls and any potential sources of bias and confounding must be modeled in analyses, along with aspects of the interventions and populations studied. Because of such controls, effect sizes from QEs are more complex than those from randomized experiments. A statistical meta-regression model that incorporates important features of the QEs under review was presented. Conclusion: Meta-analyses of quasi-experiments provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences.

Item Type:	Article
Uncontrolled Keywords:	meta-analysis,quasi-experiment,effect size,risk-of-bias,moderator variables,confounding
Faculty \ School:	Faculty of Social Sciences > School of Global Development (formerly School of International Development)
UEA Research Groups:	Faculty of Social Sciences > Research Groups > Gender and Development Faculty of Social Sciences > Research Groups > Impact Evaluation
Depositing User:	Pure Connector
Date Deposited:	06 Apr 2017 06:58
Last Modified:	22 Oct 2022 01:17
URI:	https://ueaeprints.uea.ac.uk/id/eprint/63170
DOI:	10.1016/j.jclinepi.2017.02.014

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