| HGLM versus conditional estimators for the analysis of clustered binary data. | |
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MedLine Citation:
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PMID: 15696505 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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Weechang Kang; Moo-Song Lee; Youngjo Lee |
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Publication Detail:
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Type: Comparative Study; Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Statistics in medicine Volume: 24 ISSN: 0277-6715 ISO Abbreviation: Stat Med Publication Date: 2005 Mar |
Date Detail:
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Created Date: 2005-02-16 Completed Date: 2005-05-17 Revised Date: 2007-11-15 |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: England |
Other Details:
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Languages: eng Pagination: 741-52 Citation Subset: IM |
Copyright Information:
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Copyright (c) 2004 John Wiley & Sons, Ltd. |
Affiliation:
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Department of Information and Statistics, Daejeon University, Daejeon 300-716, Korea. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Age Factors Clinical Trials as Topic / methods Cluster Analysis Cross-Over Studies Data Interpretation, Statistical* Drug Therapy Female Humans Male 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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