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ERIC Number: EJ951761
Record Type: Journal
Publication Date: 2010-Oct
Pages: 34
Abstractor: As Provided
Reference Count: 50
ISSN: ISSN-1076-9986
Multilevel Growth Mixture Models for Classifying Groups
Palardy, Gregory J.; Vermunt, Jeroen K.
Journal of Educational and Behavioral Statistics, v35 n5 p532-565 Oct 2010
This article introduces a multilevel growth mixture model (MGMM) for classifying both the individuals and the groups they are nested in. Nine variations of the general model are described that differ in terms of categorical and continuous latent variable specification within and between groups. An application in the context of school effectiveness research is presented. Schools are classified into three Type B effectiveness categories based on their mean student mathematics achievement growth trajectories, controlling for differences in students' backgrounds across schools. The classification outcome is regressed on a set of school practice variables to investigate the association between practices and cognitive development. Various issues related to model specification are discussed, including the use of covariates to identify substantively meaningful classes. (Contains 12 notes, 2 figures and 9 tables.)
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Early Childhood Education; Elementary Education; Elementary Secondary Education; Grade 1; Middle Schools; Primary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Early Childhood Longitudinal Survey