Variance estimation for clustered recurrent event data with a small number of clusters

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dc.contributor.author Schaubel, Douglas E. en_US
dc.date.accessioned 2006-12-07T16:51:57Z
dc.date.available 2006-12-07T16:51:57Z
dc.date.issued 2005-10-15 en_US
dc.identifier.citation Schaubel, Douglas E. (2005)."Variance estimation for clustered recurrent event data with a small number of clusters." Statistics in Medicine 24(19): 3037-3051. <http://hdl.handle.net/2027.42/48761> en_US
dc.identifier.issn 0277-6715 en_US
dc.identifier.issn 1097-0258 en_US
dc.identifier.uri http://hdl.handle.net/2027.42/48761
dc.identifier.uri http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=16149126&dopt=citation en_US
dc.description.abstract Often in biomedical studies, the event of interest is recurrent and within-subject events cannot usually be assumed independent. In semi-parametric estimation of the proportional rates model, a working independence assumption leads to an estimating equation for the regression parameter vector, with within-subject correlation accounted for through a robust (sandwich) variance estimator; these methods have been extended to the case of clustered subjects. We consider variance estimation in the setting where subjects are clustered and the study consists of a small number of moderate-to-large-sized clusters. We demonstrate through simulation that the robust estimator is quite inaccurate in this setting. We propose a corrected version of the robust variance estimator, as well as jackknife and bootstrap estimators. Simulation studies reveal that the corrected variance is considerably more accurate than the robust estimator, and slightly more accurate than the jackknife and bootstrap variance. The proposed methods are used to compare hospitalization rates between Canada and the U.S. in a multi-centre dialysis study. Copyright © 2005 John Wiley & Sons, Ltd. en_US
dc.format.extent 129120 bytes
dc.format.extent 3118 bytes
dc.format.mimetype application/pdf
dc.format.mimetype text/plain
dc.language.iso en_US
dc.publisher John Wiley & Sons, Ltd. en_US
dc.subject.other Mathematics and Statistics en_US
dc.title Variance estimation for clustered recurrent event data with a small number of clusters en_US
dc.type Article en_US
dc.rights.robots IndexNoFollow en_US
dc.subject.hlbsecondlevel Medicine (General) en_US
dc.subject.hlbsecondlevel Statistics and Numeric Data en_US
dc.subject.hlbsecondlevel Public Health en_US
dc.subject.hlbtoplevel Health Sciences en_US
dc.subject.hlbtoplevel Science en_US
dc.subject.hlbtoplevel Social Sciences en_US
dc.description.peerreviewed Peer Reviewed en_US
dc.contributor.affiliationum Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109-2029, U.S.A. ; Department of Biostatistics, University of Michigan, 1420 Washington Heights, M4140 SPH-2, Ann Arbor, MI 48109-2029, U.S.A. en_US
dc.identifier.pmid 16149126 en_US
dc.description.bitstreamurl http://deepblue.lib.umich.edu/bitstream/2027.42/48761/1/2157_ftp.pdf en_US
dc.identifier.doi http://dx.doi.org/10.1002/sim.2157 en_US
dc.identifier.source Statistics in Medicine en_US
dc.owningcollname Interdisciplinary and Peer-Reviewed
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