Factorial analyses of treatment effects under independent right-censoring. (February 2020)

• Record Type: Journal Article
• Authors: Dobler, Dennis; Pauly, Markus
• Is Part Of: Statistical methods in medical research. Volume 29:Number 2(2020)
• Page Start: 325
• Page End: 343
• Publication Date: 2020-02
• Subjects: Factorial designs -- Kaplan–Meier estimator -- nonparametric statistics -- quadratic forms -- wild bootstrap; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280219831316
• Languages: English
• ISSNs: 0962-2802

Abstract

This paper introduces new effect parameters for factorial survival designs with possibly right-censored time-to-event data. In the special case of a two-sample design, it coincides with the concordance or Wilcoxon parameter in survival analysis. More generally, the new parameters describe treatment or interaction effects and we develop estimates and tests to infer their presence. We rigorously study their asymptotic properties and additionally suggest wild bootstrapping for a consistent and distribution-free application of the inference procedures. The small sample performance is discussed based on simulation results. The practical usefulness of the developed methodology is exemplified on a data example about patients with colon cancer by conducting one- and two-factorial analyses.