Streamlined variance calculations for semiparametric mixed models

Smith, ADAC; Wand, MP

Streamlined variance calculations for semiparametric mixed models

Smith, ADAC Wand, MP

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Publication Type:: Journal Article
Citation:: Statistics in Medicine, 2008, 27 (3), pp. 435 - 448
Issue Date:: 2008-02-10

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Field	Value	Language
dc.contributor.author	Smith, ADAC	en_US
dc.contributor.author	Wand, MP https://orcid.org/0000-0003-2555-896X	en_US
dc.date.issued	2008-02-10	en_US
dc.identifier.citation	Statistics in Medicine, 2008, 27 (3), pp. 435 - 448	en_US
dc.identifier.issn	0277-6715	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14518
dc.description.abstract	Semiparametric mixed model analysis benefits from variability estimates such as standard errors of effect estimates and variability bars to accompany curve estimates. We show how the underlying variance calculations can be done extremely efficiently compared with the direct naïve approach. These streamlined calculations are linear in the number of subjects, representing a two orders of magnitude improvement. Copyright © 2007 John Wiley & Sons, Ltd.	en_US
dc.relation.ispartof	Statistics in Medicine	en_US
dc.relation.isbasedon	10.1002/sim.2925	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.subject.mesh	Spine	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Models, Statistical	en_US
dc.subject.mesh	Linear Models	en_US
dc.subject.mesh	Bone Density	en_US
dc.subject.mesh	Algorithms	en_US
dc.subject.mesh	New South Wales	en_US
dc.title	Streamlined variance calculations for semiparametric mixed models	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	27	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1117 Public Health and Health Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	27	en_US

Abstract:

Semiparametric mixed model analysis benefits from variability estimates such as standard errors of effect estimates and variability bars to accompany curve estimates. We show how the underlying variance calculations can be done extremely efficiently compared with the direct naïve approach. These streamlined calculations are linear in the number of subjects, representing a two orders of magnitude improvement. Copyright © 2007 John Wiley & Sons, Ltd.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/14518