期刊名称：Sankhya. Series B, applied and interdisciplinary statistics
印刷版ISSN：0976-8386
电子版ISSN：0976-8394
出版年度：2017
卷号：79
期号：2
页码：190-216
DOI：10.1007/s13571-017-0132-3
语种：English
出版社：Indian Statistical Institute
摘要：AbstractIn this paper we consider simultaneous analysis of survival time and binary longitudinal outcome where random effects are introduced to account for the dependence between the two different types of outcomes due to unobserved factors and assumed to follow a Gaussian distribution with mean zero. The estimator based on maximum likelihood approach using an Expectation-Maximization algorithm is consistent and asymptotically normally distributed. However, the EM algorithm may be intensive on numerical integrations with large sample sizes and large numbers of longitudinal observations per subject. We develop a more computationally efficient estimation procedure based on a penalized likelihood obtained by Laplace approximation. Through simulation studies, we compare numerical performances on the computing time, bias, and mean squared error from the proposed penalized likelihood estimation procedure and the EM algorithm of maximum likelihood estimation. We also illustrate the proposed approach with a liver transplantation data set.
关键词：Keywords and phrasesEnGeneralized linear mixed modelLaplace approximationPenalized likelihood estimatorRandom effectSimultaneous modelingStratified Cox proportional hazards model
