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pubmed-article:16918913pubmed:abstractTextCase-control studies augmented by the values of responses and covariates from family members allow investigators to study the association between the response and genetics and environment by relating differences in the response directly to within-family differences in covariates. However, existing approaches for case-control family data parameterize covariate effects in terms of the marginal probability of response, the same effects that one estimates from standard case-control studies. This article focuses on the estimation of family-specific covariate effects and develops efficient methods to fit family-specific models such as binary mixed-effects models. We also extend the approach to cover any setting where one has a fully specified model for the vector of responses in a family. We illustrate our approach using data from a case-control family study of brain cancer and consider the use of weighted and conditional likelihood methods as alternatives.lld:pubmed
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pubmed-article:16918913pubmed:authorpubmed-author:ScottA JAJlld:pubmed
pubmed-article:16918913pubmed:authorpubmed-author:NeuhausJ MJMlld:pubmed
pubmed-article:16918913pubmed:authorpubmed-author:WildC JCJlld:pubmed
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pubmed-article:16918913pubmed:volume62lld:pubmed
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pubmed-article:16918913pubmed:pagination488-94lld:pubmed
pubmed-article:16918913pubmed:dateRevised2006-11-15lld:pubmed
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pubmed-article:16918913pubmed:year2006lld:pubmed
pubmed-article:16918913pubmed:articleTitleFamily-specific approaches to the analysis of case-control family data.lld:pubmed
pubmed-article:16918913pubmed:affiliationDepartment of Epidemiology and Biostatistics, University of California, San Francisco, California 94143-0560, USA. john@biostat.ucsf.edulld:pubmed
pubmed-article:16918913pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:16918913pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed
pubmed-article:16918913pubmed:publicationTypeResearch Support, N.I.H., Extramurallld:pubmed
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