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Estimating restricted mean treatment effects with additive-multiplicative hazards models

Author

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  • Jinhong Li
  • Jicai Liu
  • Yanbo Pei
  • Riquan Zhang

Abstract

The difference in restricted mean survival times between two groups is often of inherent interest in epidemiologic and medical studies. In this paper, we propose a general additive-multiplicative hazards (AMHs) regression model to estimate the restricted mean treatment effects, where the survival time is subject to both dependent and independent censoring. The AMH specifies an additive and multiplicative form on the hazard functions for the survival and censored times associated with covariates, which contains the proportional hazards model and the additive hazards model. By an inverse probability censoring weights scheme, we obtain the estimators of the regression parameters and the restricted mean treatment effects. We establish the large sample properties of the proposed estimators. Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed procedures and the primary biliary cirrhosis patients data are analyzed for illustration.

Suggested Citation

  • Jinhong Li & Jicai Liu & Yanbo Pei & Riquan Zhang, 2022. "Estimating restricted mean treatment effects with additive-multiplicative hazards models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 34(4), pages 1015-1035, October.
    • Handle: RePEc:taf:gnstxx:v:34:y:2022:i:4:p:1015-1035
    DOI: 10.1080/10485252.2022.2108810
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