Document Detail


Analysis of recurrent gap time data using the weighted risk-set method and the modified within-cluster resampling method.
MedLine Citation:
PMID:  20963733     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
The gap times between recurrent events are often of primary interest in medical and epidemiology studies. The observed gap times cannot be naively treated as clustered survival data in analysis because of the sequential structure of recurrent events. This paper introduces two important building blocks, the averaged counting process and the averaged at-risk process, for the development of the weighted risk-set (WRS) estimation methods. We demonstrate that with the use of these two empirical processes, existing risk-set based methods for univariate survival time data can be easily extended to analyze recurrent gap times. Additionally, we propose a modified within-cluster resampling (MWCR) method that can be easily implemented in standard software. We show that the MWCR estimators are asymptotically equivalent to the WRS estimators. An analysis of hospitalization data from the Danish Psychiatric Central Register is presented to illustrate the proposed methods.
Authors:
Xianghua Luo; Chiung-Yu Huang
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Statistics in medicine     Volume:  30     ISSN:  1097-0258     ISO Abbreviation:  Stat Med     Publication Date:  2011 Feb 
Date Detail:
Created Date:  2011-01-12     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  301-11     Citation Subset:  IM    
Copyright Information:
2010 John Wiley & Sons, Ltd.
Affiliation:
Division of Biostatistics, School of Public Health, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN 55455, U.S.A. luox0054@umn.edu
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