ANALYSIS OF REGRESSION DISCONTINUITY DESIGNS USING CENSORED DATA.

ABSTRACT: In many medical and scientific settings, the choice of treatment or intervention may be determined by a covariate threshold. For example, elderly men may receive more thorough diagnosis if their prostate-specific antigen (PSA) level is high. In these cases, the causal treatment effect is often of great interest, especially when there is a lack of evidence from randomized clinical trials. From the social science literature, a class of methods known as regression discontinuity (RD) designs can be used to estimate the treatment effect in this situation. Under certain assumptions, such an estimand enjoys a causal interpretation. We show how to estimate causal effects under the regression discontinuity design for censored data. The proposed estimation procedure employs a class of censoring unbi

SUBMITTER: Cho Y 

PROVIDER: S-EPMC9221554 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature