Document Detail

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.
MedLine Citation:
PMID:  20213705     Owner:  NLM     Status:  MEDLINE    
We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.
Yongling Xiao; Michal Abrahamowicz
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Statistics in medicine     Volume:  29     ISSN:  1097-0258     ISO Abbreviation:  Stat Med     Publication Date:  2010 Mar 
Date Detail:
Created Date:  2010-03-15     Completed Date:  2010-06-18     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  915-23     Citation Subset:  IM    
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada H3A 1A2.
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MeSH Terms
Arthritis, Rheumatoid / diagnosis,  epidemiology
Cluster Analysis*
Computer Simulation / statistics & numerical data
Confidence Intervals
Proportional Hazards Models*
Quebec / epidemiology
Regression Analysis*
Software / statistics & numerical data
Grant Support
MOP-8127//Canadian Institutes of Health Research

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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