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QUASI-EXPERIMENTAL STUDY DESIGNS SERIES-PAPER 7: ASSESSING THE ASSUMPTIONS
Barnighausen, Till et al. | Date Issued: 2017
Author
Barnighausen, Till
Oldenburg, Catherine
Tugwell, Peter
Bommer, Christian
Ebert, Cara
Barreto, Maurício Lima
Djimeu, Eric
Haber, Noah
Waddington, Hugh
Rockers, Peter
Sianesi, Barbara
Bor, Jacob
Fink, Günther
Valentine, Jeffrey
Tanner, Jeffrey
Stanley, Tom
Sierra, Eduardo
Tchetgen, Eric Tchetgen
Atun, Rifat
Vollmer, Sebastian
Affilliation
Heidelberg University. Faculty of Medicine. Institute of Public Health. Heidelberg, Germany / School of Public Health. Harvard T.H. Chan. Department of Global Health and Population. Boston, USA / Africa Health Research Institute. Somkhele, South África.
University of Califórnia. Francis I. Proctor Foundation. San Francisco, San Francisco, USA.
University of Ottawa. Department of Medicine. Ottawa, Canada.
University of Göttingen. Department of Economics. Göttingen, Germany.
Federal University of Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brazil / National Institute in Science, Technology and Innovation in Health. Salvador, BA, Brazil.
International Initiative for Impact Evaluation. London, UK / International Initiative for Impact Evaluation. Washington, DC, USA.
Harvard T.H. Chan School of Public Health. Department of Global Health and Population. Boston, USA.
International Initiative for Impact Evaluation. London, UK / International Initiative for Impact Evaluation. Washington, DC, USA.
Boston University. Center for Global Health and Development. Boston, USA.
Institute for Fiscal Studies. London, UK.
Boston University. School of Public Health. Boston, USA.
Harvard T.H. Chan School of Public Health. Department of Global Health and Population. Boston, USA.
University of Louisville. College of Education and Human Development. Louisville, USA.
World Bank. Impact Evaluation. Washington DC, USA.
Hendrix College. Conway, AR, USA.
Freiburg University. Centre for Medicine and Society. Freiburg, Germany.
Harvard T.H. Chan School of Public Health. Department of Global Health and Population. Boston, USA.
Harvard T.H. Chan School of Public Health. Department of Global Health and Population. Boston, USA.
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.
Keywords in Portuguese
Projetos de pesquisa
Epidemiologia
Assistencia médica
Sistemas de saúde
 
Keywords
Research Design
Epidemiology
Health care
Health systems
 
Publisher
Elsevier
Citation
BARNIGHAUSEN, Till et al. Quasi-experimental study designs series-paper 7: assessing the assumptions. Journal of Clinical Epidemiology, v. 89, p. 1-14, 2017.
DOI
10.1016/j.jclinepi.2017.02.017
ISSN
0895-4356
Notes
Barreto, Mauricio Lima. Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. “Documento produzido em parceria ou por autor vinculado à Fiocruz, mas não consta à informação no documento”.