Document Detail

Estimating local and global measures of association for bivariate interval censored data with a smooth estimate of the density.
MedLine Citation:
PMID:  18623606     Owner:  NLM     Status:  MEDLINE    
Measures of association for bivariate interval censored data have not yet been studied extensively. Betensky and Finkelstein (Statist. Med. 1999; 18:3101-3109) proposed to calculate Kendall's coefficient of concordance using a multiple imputation technique, but their method becomes computer intensive for moderate to large data sets. We suggest a different approach consisting of two steps. Firstly, a bivariate smooth estimate of the density of log-event times is determined. The smoothing technique is based on a mixture of Gaussian densities fixed on a grid with weights determined by a penalized likelihood approach. Secondly, given the smooth approximation several local and global measures of association can be estimated readily. The performance of our method is illustrated by an extensive simulation study and is applied to tooth emergence data of permanent teeth measured on 4468 children from the Signal-Tandmobiel study.
Kris Bogaerts; Emmanuel Lesaffre
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Statistics in medicine     Volume:  27     ISSN:  0277-6715     ISO Abbreviation:  Stat Med     Publication Date:  2008 Dec 
Date Detail:
Created Date:  2008-11-04     Completed Date:  2009-02-26     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  5941-55     Citation Subset:  IM    
Biostatistical Centre, Katholieke Universiteit of Leuven, Leuven, Belgium.
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MeSH Terms
Data Interpretation, Statistical*
Dental Care for Children / statistics & numerical data
Health Behavior
Models, Statistical*
Oral Health
Tooth Eruption

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

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