Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma.

Abstract:

:A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environmental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Yau KK,Ng AS

doi

10.1002/sim.932

subject

Has Abstract

pub_date

2001-06-15 00:00:00

pages

1591-607

issue

11

eissn

0277-6715

issn

1097-0258

journal_volume

20

pub_type

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