Lin, D. Y.; Ying, Zhiliang Semiparametric analysis of the additive risk model. (English) Zbl 0796.62099 Biometrika 81, No. 1, 61-71 (1994). Summary: In contrast to the proportional hazards model, the additive risk model specifies that the hazard function associated with a set of possibly time-varying covariates is the sum of, rather than the product of, the baseline hazard function and the regression function of covariates. This formulation describes a different aspect of the association between covariates and the failure time than the proportional hazards model, and is more plausible than the latter for many applications.In the present paper, simple procedures with high efficiencies are developed for making inference about the regression parameters under the additive risk model with an unspecified baseline hazard function. The subject-specific survival estimation is also studied. The proposed techniques resemble the partial-likelihood-based methods for the proportional hazards model. A real example is provided. Cited in 8 ReviewsCited in 217 Documents MSC: 62P10 Applications of statistics to biology and medical sciences; meta analysis 62G05 Nonparametric estimation Keywords:adaptive estimation; censoring; counting process; excess risk; information bound; martingale; partial likelihood; time-dependent covariate; truncation; proportional hazards model; additive risk model; time-varying covariates; failure time; regression parameters; unspecified baseline hazard function; subject-specific survival estimation; partial- likelihood-based methods PDFBibTeX XMLCite \textit{D. Y. Lin} and \textit{Z. Ying}, Biometrika 81, No. 1, 61--71 (1994; Zbl 0796.62099) Full Text: DOI