Liu, Peng; Song, Shanshan; Zhou, Yong Semiparametric additive frailty hazard model for clustered failure time data. (English. French summary) Zbl 1492.62148 Can. J. Stat. 50, No. 2, 549-571 (2022). Summary: This article proposes a flexible semiparametric additive frailty hazard model under clustered failure time data, where frailty is assumed to have an additive effect on the hazard function. When there is no frailty, this model degenerates into a semiparametric additive hazard model. Our method can deal simultaneously with both time-varying and constant covariate effects. The estimate of the covariate effects does not rely on the frailty distribution. The time-varying coefficient is estimated by utilizing the local linear technique, while we can obtain a \(\sqrt{ n} \)-consistency convergence rate of the constant-coefficient estimate by integration. Another advantage of the estimator is that it has a closed form. We establish large sample properties of the estimator and conduct simulation studies under various scenarios to demonstrate its performance. The proposed method is applied to real data for illustration. MSC: 62N01 Censored data models 62N02 Estimation in survival analysis and censored data 62G05 Nonparametric estimation 62F12 Asymptotic properties of parametric estimators Keywords:additive frailty hazard model; clustered failure time data; local linear technique; semiparametric model PDFBibTeX XMLCite \textit{P. Liu} et al., Can. J. Stat. 50, No. 2, 549--571 (2022; Zbl 1492.62148) Full Text: DOI Link