title: Quasi-experimental study designs series-paper 10: synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges.
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.
  
  
  METHODS
  We drew on studies of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of QEs, 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.
  
  
  CONCLUSIONS
  Meta-analyses of QEs provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences.
authors.affiliation: Educational Psychology and Learning Systems, College of Education, Florida State University, 3210D Stone Bldg, Tallahassee, FL 32306-4453, USA. Electronic address: bbecker@fsu.edu.
authors.forename: Betsy Jane
authors.initials: BJ
authors.lastname: Becker
authors.affiliation: Psychological and Quantitative Foundations, University of Iowa, 368 (South) Lindquist Center, Iowa City, IA 52242, USA.
authors.forename: Ariel M
authors.initials: AM
authors.lastname: Aloe
authors.affiliation: University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.
authors.forename: Maren
authors.initials: M
authors.lastname: Duvendack
authors.affiliation: Department of Economics, Hendrix College, 1600 Washington St, Conway, AR 72032, USA; School of Business and Law, Deakin University, 221 Burwood Highway, Melbourne, 3125 Victoria, Australia.
authors.forename: T D
authors.initials: TD
authors.lastname: Stanley
authors.affiliation: Counseling and Human Development, University of Louisville, 309 Porter Education Building, Louisville, KY 40292, USA.
authors.forename: Jeffrey C
authors.initials: JC
authors.lastname: Valentine
authors.affiliation: Global Health Unit, Division for Health Services, Norwegian Institute of Public Health, PO Box 4404 Nydalen, 0403 Oslo, Norway; Institute of Health and Society, University of Oslo, PO Box 1130 Blindern, 0318 Oslo, Norway.
authors.forename: Atle
authors.initials: A
authors.lastname: Fretheim
authors.affiliation: Department of Medicine, University of Ottawa, 272 Stewart St., Ottawa, Ontario, Canada K1N6K4.
authors.forename: Peter
authors.initials: P
authors.lastname: Tugwell
mesh_terms: D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D065228:Non-Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data*; D012107:Research Design
keywords: Confounding; Effect size; Meta-analysis; Moderator variables; Quasi-experiment; Risk-of-bias