Hagemeier A, Samel C, Hellmich M. The regression discontinuity design: Methods and implementation with a worked example in health services research.
Z Evid Fortbild Qual Gesundhwes 2022;
172:71-77. [PMID:
35718728 DOI:
10.1016/j.zefq.2022.04.014]
[Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/29/2022] [Accepted: 04/12/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND
The randomized controlled trial (RCT) is the gold standard in evidence-based medicine. However, this design may not be appropriate in every setting, so other methods or designs such as the regression discontinuity design (RDD) are required.
METHOD
The aim of this article is to introduce the RDD, summarise methodology in the context of health services research and present a worked example using the statistic software SPSS (Examples for R and Stata in the Appendix A). The mathematical notations of sharp and fuzzy RDD as well as their distinction are presented. Furthermore, examples from the literature and recent studies are highlighted, and both advantages and disadvantages of the design are discussed.
APPLICATION
The RDD consists of four essential steps: 1. Determine feasibility; 2. Note possible treatment manipulation, 3. Check for the treatment effect, and 4. Fit the regression models to measure the treatment effect.
CONCLUSION
The RDD comes as an alternative for studies in health service research where an RCT cannot be conducted, but a threshold-based comparison can be made.
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