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ERIC Number: EJ1300035
Record Type: Journal
Publication Date: 2021-Aug
Pages: 28
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0013-1644
EISSN: N/A
Available Date: N/A
Combined Approach to Multi-Informant Data Using Latent Factors and Latent Classes: Trifactor Mixture Model
Kim, Eunsook; von der Embse, Nathaniel
Educational and Psychological Measurement, v81 n4 p728-755 Aug 2021
Although collecting data from multiple informants is highly recommended, methods to model the congruence and incongruence between informants are limited. Bauer and colleagues suggested the trifactor model that decomposes the variances into common factor, informant perspective factors, and item-specific factors. This study extends their work to the trifactor mixture model that combines the trifactor model and the mixture model. This combined approach allows researchers to investigate the common and unique perspectives of multiple informants on targets using latent factors and simultaneously take into account potential heterogeneity of targets using latent classes. We demonstrate this model using student self-rated and teacher-rated academic behaviors (N = 24,094). Model specification and testing procedures are explicated in detail. Methodological and practical issues in conducting the trifactor mixture analysis are discussed.
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://bibliotheek.ehb.be:2814
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A