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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Regression discontinuity designs in epidemiology: Causal inference without randomized trials
Epidemiology, Volume 25, No. 5, Year 2014
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Description
When patients receive an intervention based on whether they score below or above some threshold value on a continuously measured random variable, the intervention will be randomly assigned for patients close to the threshold. The regression discontinuity design exploits this fact to estimate causal treatment effects. In spite of its recent proliferation in economics, the regression discontinuity design has not been widely adopted in epidemiology. We describe regression discontinuity, its implementation, and the assumptions required for causal inference. We show that regression discontinuity is generalizable to the survival and nonlinear models that are mainstays of epidemiologic analysis. We then present an application of regression discontinuity to the much-debated epidemiologic question of when to start HIV patients on antiretroviral therapy. Using data from a large South African cohort (2007-2011), we estimate the causal effect of early versus deferred treatment eligibility on mortality. Patients whose first CD4 count was just below the 200 cells/μL CD4 count threshold had a 35% lower hazard of death (hazard ratio = 0.65 [95% confidence interval = 0.45-0.94]) than patients presenting with CD4 counts just above the threshold. We close by discussing the strengths and limitations of regression discontinuity designs for epidemiology. Copyright © 2014 by Lippincott Williams & Wilkins.
Authors & Co-Authors
Bor, Jacob H.
United States, Boston
School of Public Health
South Africa, Durban
Africa Health Research Institute
United States, Boston
Harvard T.h. Chan School of Public Health
Moscoe, Ellen
United States, Boston
Harvard T.h. Chan School of Public Health
Mutevedzi, Portia Chipo
South Africa, Durban
Africa Health Research Institute
Newell, Marie Louise
South Africa, Durban
Africa Health Research Institute
United Kingdom, Southampton
University of Southampton, Faculty of Medicine
Bärnighausen, Till Winfried
South Africa, Durban
Africa Health Research Institute
United States, Boston
Harvard T.h. Chan School of Public Health
Statistics
Citations: 133
Authors: 5
Affiliations: 4
Identifiers
Doi:
10.1097/EDE.0000000000000138
ISSN:
10443983
e-ISSN:
15315487
Research Areas
Environmental
Infectious Diseases
Study Design
Randomised Control Trial
Cohort Study