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Activity Number: 215 - Non- and Semiparametric Methods to Accommodate Dependency and Heterogeneity in Complex Data
Type: Invited
Date/Time: Monday, July 30, 2018 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #326514 Presentation
Title: Goodness-of-Fit Tests in Proportional Hazards Models with Random Effects
Author(s): Ingrid Van Keilegom* and Wenceslao Gonzalez Manteiga and Maria Dolores Martinez Miranda
Companies: KU Leuven and University of Santiago de Compostela and University of Granada
Keywords: Frailty; Proportional hazards; Cox regression; Random effects; Orthogonal polynomials; Survival analysis

This paper deals with testing the functional form of the covariate effects in a Cox proportional hazards model with random effects, like for instance a shared frailty model. We assume that the responses are clustered and incomplete due to right censoring. The estimation of the model under the null (parametric covariate effect) and the alternative (non-parametric effect) is performed using the full marginal likelihood. Under the alternative, the non-parametric covariate effects are estimated using orthogonal expansions. The test statistic is the likelihood ratio statistic, and its distribution is approximated using a bootstrap method. The performance of the proposed testing procedure is studied through simulations. The method is also applied on real data coming from a study on the chronic granulotomous disease.

Authors who are presenting talks have a * after their name.

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