Pseudo-full likelihood estimation for prospective survival analysis with a general semiparametric shared frailty model: Asymptotic theory

David M. Zucker; Malka Gorfine; Li Hsu

doi:10.1016/j.jspi.2007.08.005

Pseudo-full likelihood estimation for prospective survival analysis with a general semiparametric shared frailty model: Asymptotic theory

David M. Zucker^*, Malka Gorfine, Li Hsu

^*Corresponding author for this work

Department of Statistics

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

In this work we present a simple estimation procedure for a general frailty model for analysis of prospective correlated failure times. Earlier work showed this method to perform well in a simulation study. Here we provide rigorous large-sample theory for the proposed estimators of both the regression coefficient vector and the dependence parameter, including consistent variance estimators.

Original language	English
Pages (from-to)	1998-2016
Number of pages	19
Journal	Journal of Statistical Planning and Inference
Volume	138
Issue number	7
DOIs	https://doi.org/10.1016/j.jspi.2007.08.005
State	Published - 1 Jul 2008

Keywords

Correlated failure times
EM algorithm
Frailty model
Prospective family study
Survival analysis

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10.1016/j.jspi.2007.08.005

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abstract = "In this work we present a simple estimation procedure for a general frailty model for analysis of prospective correlated failure times. Earlier work showed this method to perform well in a simulation study. Here we provide rigorous large-sample theory for the proposed estimators of both the regression coefficient vector and the dependence parameter, including consistent variance estimators.",

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AU - Gorfine, Malka

AU - Hsu, Li

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KW - Correlated failure times

KW - EM algorithm

KW - Frailty model

KW - Prospective family study

KW - Survival analysis

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ER -

Pseudo-full likelihood estimation for prospective survival analysis with a general semiparametric shared frailty model: Asymptotic theory

Abstract

Keywords

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