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

✍ Scribed by Jianwen Cai; Haibo Zhou; C. E. Davis

Publisher: John Wiley and Sons
Year: 1997
Tongue: English
Weight: 130 KB
Volume: 16
Category: Article
ISSN: 0277-6715
DOI: 10.1002/(sici)1097-0258(19970915)16:17<2009::aid-sim606>3.0.co;2-r

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✦ Synopsis

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.

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