Estimating the mean hazard ratio parameters for clustered survival data with random clusters.

Abstract:

:We consider a latent variable hazard model for clustered survival data where clusters are a random sample from an underlying population. We allow interactions between the random cluster effect and covariates. We use a maximum pseudo-likelihood estimator to estimate the mean hazard ratio parameters. We propose a bootstrap sampling scheme to obtain an estimate of the variance of the proposed estimator. Application of this method in large multi-centre clinical trials allows one to assess the mean treatment effect, where we consider participating centres as a random sample from an underlying population. We evaluate properties of the proposed estimators via extensive simulation studies. A real data example from the Studies of Left Ventricular Dysfunction (SOLVD) Prevention Trial illustrates the method.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Cai J,Zhou H,Davis CE

doi

10.1002/(sici)1097-0258(19970915)16:17<2009::aid-s

subject

Has Abstract

pub_date

1997-09-15 00:00:00

pages

2009-20

issue

17

eissn

0277-6715

issn

1097-0258

pii

10.1002/(SICI)1097-0258(19970915)16:17<2009::AID-S

journal_volume

16

pub_type

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