A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest

A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest

When testing for reduction of the mean value structure in linear mixed models, it is common to use an asymptotic ?2 test. Such tests can, however, be very poor for small and moderate sample sizes. The pbkrtest package implements two alternatives to such approximate ?2 tests: The package implements (...

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Bibliographic Details
Main Authors: Ulrich Halekoh, Søren Højsgaard
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2014-09-01
Series:Journal of Statistical Software
Online Access:http://www.jstatsoft.org/index.php/jss/article/view/2167
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spelling doaj-6df1f5887e6141ea85273278b7bf47dd2020-11-24T23:15:10ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602014-09-0159113210.18637/jss.v059.i09771A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtestUlrich HalekohSøren HøjsgaardWhen testing for reduction of the mean value structure in linear mixed models, it is common to use an asymptotic ?2 test. Such tests can, however, be very poor for small and moderate sample sizes. The pbkrtest package implements two alternatives to such approximate ?2 tests: The package implements (1) a Kenward-Roger approximation for performing F tests for reduction of the mean structure and (2) parametric bootstrap methods for achieving the same goal. The implementation is focused on linear mixed models with independent residual errors. In addition to describing the methods and aspects of their implementation, the paper also contains several examples and a comparison of the various methods.http://www.jstatsoft.org/index.php/jss/article/view/2167
collection DOAJ
language English
format Article
sources DOAJ
author Ulrich Halekoh
Søren Højsgaard
spellingShingle Ulrich Halekoh
Søren Højsgaard
A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest
Journal of Statistical Software
author_facet Ulrich Halekoh
Søren Højsgaard
author_sort Ulrich Halekoh
title A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest
title_short A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest
title_full A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest
title_fullStr A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest
title_full_unstemmed A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest
title_sort kenward-roger approximation and parametric bootstrap methods for tests in linear mixed models the r package pbkrtest
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2014-09-01
description When testing for reduction of the mean value structure in linear mixed models, it is common to use an asymptotic ?2 test. Such tests can, however, be very poor for small and moderate sample sizes. The pbkrtest package implements two alternatives to such approximate ?2 tests: The package implements (1) a Kenward-Roger approximation for performing F tests for reduction of the mean structure and (2) parametric bootstrap methods for achieving the same goal. The implementation is focused on linear mixed models with independent residual errors. In addition to describing the methods and aspects of their implementation, the paper also contains several examples and a comparison of the various methods.
url http://www.jstatsoft.org/index.php/jss/article/view/2167
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AT sørenhøjsgaard kenwardrogerapproximationandparametricbootstrapmethodsfortestsinlinearmixedmodelstherpackagepbkrtest
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