Deakin University

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The regression discontinuity design showed to be a valid alternative to a randomized controlled trial for estimating treatment effects

journal contribution
posted on 2017-02-01, 00:00 authored by Iris L Maas, Sandra Nolte, Otto B Walter, Thomas Berger, Martin Hautzinger, Fritz Hohagen, Wolfgang Lutz, Björn Meyer, Johanna Schröder, Christina Späth, Jan Philipp Klein, Steffen Moritz, Matthias Rose
OBJECTIVES: To compare treatment effect estimates obtained from a regression discontinuity (RD) design with results from an actual randomized controlled trial (RCT). STUDY DESIGN AND SETTING: Data from an RCT (EVIDENT), which studied the effect of an Internet intervention on depressive symptoms measured with the Patient Health Questionnaire (PHQ-9), were used to perform an RD analysis, in which treatment allocation was determined by a cutoff value at baseline (PHQ-9 = 10). A linear regression model was fitted to the data, selecting participants above the cutoff who had received the intervention (n = 317) and control participants below the cutoff (n = 187). Outcome was PHQ-9 sum score 12 weeks after baseline. Robustness of the effect estimate was studied; the estimate was compared with the RCT treatment effect. RESULTS: The final regression model showed a regression coefficient of -2.29 [95% confidence interval (CI): -3.72 to -.85] compared with a treatment effect found in the RCT of -1.57 (95% CI: -2.07 to -1.07). CONCLUSION: Although the estimates obtained from two designs are not equal, their confidence intervals overlap, suggesting that an RD design can be a valid alternative for RCTs. This finding is particularly important for situations where an RCT may not be feasible or ethical as is often the case in clinical research settings.



Journal of clinical epidemiology






Amsterdam, The Netherlands





Publication classification

C Journal article, C1.1 Refereed article in a scholarly journal

Copyright notice

2016, Elsevier Inc.