A maximum likelihood latent variable regression model for multiple informants

Horton, NJ; Roberts, K; Ryan, L; Suglia, SF; Wright, RJ

A maximum likelihood latent variable regression model for multiple informants

Horton, NJ Roberts, K Ryan, L

Suglia, SF Wright, RJ

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Publication Type:: Journal Article
Citation:: Statistics in Medicine, 2008, 27 (24), pp. 4992 - 5004
Issue Date:: 2008-12-30

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Field	Value	Language
dc.contributor.author	Horton, NJ	en_US
dc.contributor.author	Roberts, K	en_US
dc.contributor.author	Ryan, L https://orcid.org/0000-0001-5957-2490	en_US
dc.contributor.author	Suglia, SF	en_US
dc.contributor.author	Wright, RJ	en_US
dc.date.issued	2008-12-30	en_US
dc.identifier.citation	Statistics in Medicine, 2008, 27 (24), pp. 4992 - 5004	en_US
dc.identifier.issn	0277-6715	en_US
dc.identifier.uri	http://hdl.handle.net/10453/23497
dc.description.abstract	Studies pertaining to childhood psychopathology often incorporate information from multiple sources (or informants). For example, measurement of some factor of particular interest might be collected from parents, teachers as well as the children being studied. We propose a latent variable modeling framework to incorporate multiple informant predictor data. Several related models are presented, and likelihood ratio tests are introduced to formally compare fit. The incorporation of partially observed subjects is addressed under a variety of missing data mechanisms. The methods are motivated by and applied to a study of the association of chronic exposure to violence on asthma in children. Copyright © 2008 John Wiley & Sons, Ltd.	en_US
dc.relation.ispartof	Statistics in Medicine	en_US
dc.relation.isbasedon	10.1002/sim.3324	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Asthma	en_US
dc.subject.mesh	Adolescent	en_US
dc.subject.mesh	Bias	en_US
dc.subject.mesh	Child	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Likelihood Functions	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Psychometrics	en_US
dc.subject.mesh	Psychopathology	en_US
dc.subject.mesh	Regression Analysis	en_US
dc.subject.mesh	Surveys and Questionnaires	en_US
dc.subject.mesh	Violence	en_US
dc.title	A maximum likelihood latent variable regression model for multiple informants	en_US
dc.type	Journal Article
utslib.citation.volume	24	en_US
utslib.citation.volume	27	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1117 Public Health and Health Services	en_US
dc.location.activity	Wellington, New Zealand
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	24	en_US
pubs.publication-status	Published	en_US
pubs.volume	27	en_US

Abstract:

Studies pertaining to childhood psychopathology often incorporate information from multiple sources (or informants). For example, measurement of some factor of particular interest might be collected from parents, teachers as well as the children being studied. We propose a latent variable modeling framework to incorporate multiple informant predictor data. Several related models are presented, and likelihood ratio tests are introduced to formally compare fit. The incorporation of partially observed subjects is addressed under a variety of missing data mechanisms. The methods are motivated by and applied to a study of the association of chronic exposure to violence on asthma in children. Copyright © 2008 John Wiley & Sons, Ltd.

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

http://hdl.handle.net/10453/23497