Document Detail

HGLM versus conditional estimators for the analysis of clustered binary data.
MedLine Citation:
PMID:  15696505     Owner:  NLM     Status:  MEDLINE    
Clustered binary data arise frequently in medical research such as cross-over clinical trials and twin studies. For the analysis of such data either a random-effects model or a conditional likelihood approach can be used. In this paper, we compare numerically the random-effects model estimator and the conditional likelihood estimator and discuss their relative merits for the analysis of binary data.
Weechang Kang; Moo-Song Lee; Youngjo Lee
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Statistics in medicine     Volume:  24     ISSN:  0277-6715     ISO Abbreviation:  Stat Med     Publication Date:  2005 Mar 
Date Detail:
Created Date:  2005-02-16     Completed Date:  2005-05-17     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  741-52     Citation Subset:  IM    
Copyright Information:
Copyright (c) 2004 John Wiley & Sons, Ltd.
Department of Information and Statistics, Daejeon University, Daejeon 300-716, Korea.
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MeSH Terms
Age Factors
Clinical Trials as Topic / methods
Cluster Analysis
Cross-Over Studies
Data Interpretation, Statistical*
Drug Therapy
Models, Statistical*
Numerical Analysis, Computer-Assisted*
Sex Factors
Skin Diseases / drug therapy
Twin Studies as Topic / methods

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

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