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, 00:00authored byIris 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.