The R Package geepack for Generalized Estimating Equations

This paper describes the core features of the R package geepack, which implements the generalized estimating equations (GEE) approach for fitting marginal generalized linear models to clustered data. Clustered data arise in many applications such as longitudinal data and repeated measures. The GEE a...

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Main Authors:	Ulrich Halekoh, Søren Højsgaard, Jun Yan
Format:	Article
Language:	English
Published:	Foundation for Open Access Statistics 2005-12-01
Series:	Journal of Statistical Software
Subjects:	generalized estimating equation random effect mixed model quasi-likelihood
Online Access:	http://www.jstatsoft.org/v15/i02/paper

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spelling	doaj-5aec1ce51f3d4c02969c2460caef23c22020-11-24T21:05:25ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602005-12-01152The R Package geepack for Generalized Estimating EquationsUlrich HalekohSøren HøjsgaardJun YanThis paper describes the core features of the R package geepack, which implements the generalized estimating equations (GEE) approach for fitting marginal generalized linear models to clustered data. Clustered data arise in many applications such as longitudinal data and repeated measures. The GEE approach focuses on models for the mean of the correlated observations within clusters without fully specifying the joint distribution of the observations. It has been widely used in statistical practice. This paper illustrates the application of the GEE approach with geepack through an example of clustered binary data.http://www.jstatsoft.org/v15/i02/papergeneralized estimating equationrandom effectmixed modelquasi-likelihood
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Ulrich Halekoh Søren Højsgaard Jun Yan
spellingShingle	Ulrich Halekoh Søren Højsgaard Jun Yan The R Package geepack for Generalized Estimating Equations Journal of Statistical Software generalized estimating equation random effect mixed model quasi-likelihood
author_facet	Ulrich Halekoh Søren Højsgaard Jun Yan
author_sort	Ulrich Halekoh
title	The R Package geepack for Generalized Estimating Equations
title_short	The R Package geepack for Generalized Estimating Equations
title_full	The R Package geepack for Generalized Estimating Equations
title_fullStr	The R Package geepack for Generalized Estimating Equations
title_full_unstemmed	The R Package geepack for Generalized Estimating Equations
title_sort	r package geepack for generalized estimating equations
publisher	Foundation for Open Access Statistics
series	Journal of Statistical Software
issn	1548-7660
publishDate	2005-12-01
description	This paper describes the core features of the R package geepack, which implements the generalized estimating equations (GEE) approach for fitting marginal generalized linear models to clustered data. Clustered data arise in many applications such as longitudinal data and repeated measures. The GEE approach focuses on models for the mean of the correlated observations within clusters without fully specifying the joint distribution of the observations. It has been widely used in statistical practice. This paper illustrates the application of the GEE approach with geepack through an example of clustered binary data.
topic	generalized estimating equation random effect mixed model quasi-likelihood
url	http://www.jstatsoft.org/v15/i02/paper
work_keys_str_mv	AT ulrichhalekoh therpackagegeepackforgeneralizedestimatingequations AT sørenhøjsgaard therpackagegeepackforgeneralizedestimatingequations AT junyan therpackagegeepackforgeneralizedestimatingequations AT ulrichhalekoh rpackagegeepackforgeneralizedestimatingequations AT sørenhøjsgaard rpackagegeepackforgeneralizedestimatingequations AT junyan rpackagegeepackforgeneralizedestimatingequations
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The R Package geepack for Generalized Estimating Equations

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