Survival Analysis Using Additive Risk Models.
Abstract
Cox's (1972) proportional hazards model has so far been the most popular model for the regression analysis of censored survival data. However, the additive risk model of Aalen (1980) provides a useful and biologically more plausible alternative when large sample size makes it application feasible. Let lambda(t,Y) be the hazard function for a subject whose covariates are given by Y = (Y sub 1,...,Y sub p). Aalen's model stipulates that lambda(t) =Y alpha(t), where alpha = (alpha sub 1,..., alpha sub p) is an unknown vector of hazard functions. This paper discusses inference for alpha sub 1,..., alpha sub p) based on continuous and grouped data. Asymptotic distribution results are developed using the theory of counting and used to provide confidence bands for the cumulative hazard functions. The method is applied to data on the incidence of cancer mortality among Japanese atomic bomb survivors. Keywords: Monte Carlo method; Multivariate analysis; Martingale methods.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 1987
- Accession Number
- ADA180750
Entities
People
- Fred W. Huffer
- Ian W. Mckeague
Organizations
- Florida State University