CausalCmprsk: An R package for nonparametric and Cox-based estimation of average treatment effects in competing risks data.

ABSTRACT:

Background and objective

Competing risks data arise in both observational and experimental clinical studies with time-to-event outcomes, when each patient might follow one of the multiple mutually exclusive competing paths. Ignoring competing risks in the analysis can result in biased conclusions. In addition, possible confounding bias of the treatment-outcome relationship has to be addressed, when estimating treatment effects from observational data. In order to provide tools for estimation of average treatment effects on time-to-event outcomes in the presence of competing risks, we developed the R package causalCmprsk. We illustrate the package functionality in the estimation of effects of a right heart catheterization procedure on discharge and in-hospital death from observation

SUBMITTER: Vakulenko-Lagun B 

PROVIDER: S-EPMC10841064 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature