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Title: R Package multgee: A Generalized Estimating Equations Solver for Multinomial Responses | Journal of Statistical Software

Open Graph Title: R Package multgee: A Generalized Estimating Equations Solver for Multinomial Responses by Anestis Touloumis

Open Graph Description: The R package multgee implements the local odds ratios generalized estimating equations (GEE) approach proposed by Touloumis, Agresti, and Kateri (2013), a GEE approach for correlated multinomial responses that circumvents theoretical and practical limitations of the GEE method. A main strength of multgee is that it provides GEE routines for both ordinal (ordLORgee) and nominal (nomLORgee) responses, while relevant other softwares in R and SAS are restricted to ordinal responses under a marginal cumulative link model specification. In addition, multgee offers a marginal adjacent categories logit model for ordinal responses and a marginal baseline category logit model for nominal responses. Further, utility functions are available to ease the local odds ratios structure selection (intrinsic.pars) and to perform a Wald type goodness-of-fit test between two nested GEE models (waldts). We demonstrate the application of multgee through a clinical trial with clustered ordinal multinomial responses.

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DC.Creator.PersonalNameAnestis Touloumis
DC.Date.created2015-03-20
DC.Date.dateSubmitted2013-06-08
DC.Date.issued2015-03-20
DC.Date.modified2015-03-20
DC.DescriptionThe R package multgee implements the local odds ratios generalized estimating equations (GEE) approach proposed by Touloumis, Agresti, and Kateri (2013), a GEE approach for correlated multinomial responses that circumvents theoretical and practical limitations of the GEE method. A main strength of multgee is that it provides GEE routines for both ordinal (ordLORgee) and nominal (nomLORgee) responses, while relevant other softwares in R and SAS are restricted to ordinal responses under a marginal cumulative link model specification. In addition, multgee offers a marginal adjacent categories logit model for ordinal responses and a marginal baseline category logit model for nominal responses. Further, utility functions are available to ease the local odds ratios structure selection (intrinsic.pars) and to perform a Wald type goodness-of-fit test between two nested GEE models (waldts). We demonstrate the application of multgee through a clinical trial with clustered ordinal multinomial responses.
DC.FormatSP
DC.Identifierv064i08
DC.Identifier.pageNumber1 - 14
DC.Identifier.DOI10.18637/jss.v064.i08
DC.Identifier.URIhttps://www.jstatsoft.org/index.php/jss/article/view/v064i08
DC.Languageen
DC.RightsCopyright (c) 2013 Anestis Touloumis
DC.SourceJournal of Statistical Software
DC.Source.ISSN1548-7660
DC.Source.Volume64
DC.Source.URIhttps://www.jstatsoft.org/index.php/jss
DC.TitleR Package multgee: A Generalized Estimating Equations Solver for Multinomial Responses
DC.TypeText.Serial.Journal
DC.Type.articleTypeArticles
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citation_journal_titleJournal of Statistical Software
citation_journal_abbrevJ. Stat. Soft.
citation_issn1548-7660
citation_authorAnestis Touloumis
citation_titleR Package multgee: A Generalized Estimating Equations Solver for Multinomial Responses
citation_languageen
citation_date2015/03/20
citation_volume64
citation_firstpage1
citation_lastpage14
citation_doi10.18637/jss.v064.i08
citation_abstract_html_urlhttps://www.jstatsoft.org/index.php/jss/article/view/v064i08

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