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ERIC Number: EJ973869
Record Type: Journal
Publication Date: 2012-Aug
Pages: 25
Abstractor: As Provided
Reference Count: 56
ISSN: ISSN-1076-9986
Profile-Likelihood Approach for Estimating Generalized Linear Mixed Models with Factor Structures
Jeon, Minjeong; Rabe-Hesketh, Sophia
Journal of Educational and Behavioral Statistics, v37 n4 p518-542 Aug 2012
In this article, the authors suggest a profile-likelihood approach for estimating complex models by maximum likelihood (ML) using standard software and minimal programming. The method works whenever setting some of the parameters of the model to known constants turns the model into a standard model. An important class of models that can be estimated this way is generalized linear mixed models with factor structures. Such models are useful in educational research, for example, for estimation of value-added teacher or school effects with persistence parameters and for analysis of large-scale assessment data using multilevel item response models with discrimination parameters. The authors describe the profile-likelihood approach, implement it in the R software, and apply the method to longitudinal data and binary item response data. Simulation studies and comparison with "gllamm" show that the profile-likelihood method performs well in both types of applications. The authors also briefly discuss other types of models that can be estimated using the profile-likelihood idea. (Contains 3 figures and 4 tables.)
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: Elementary Education; Elementary Secondary Education; High Schools; Junior High Schools; Middle Schools; Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Netherlands; South Korea