ERIC Number: EJ1085799
Record Type: Journal
Publication Date: 2016-Feb
Abstractor: As Provided
Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale
Huang, Francis L.; Cornell, Dewey G.
Journal of Psychoeducational Assessment, v34 n1 p3-14 Feb 2016
Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on the level of analysis. The current study illustrates the application of multilevel factor analytic techniques using a large statewide sample of middle school students (n = 39,364) from 423 schools. Both multilevel exploratory and confirmatory factor analyses were used to investigate the factor structure of the Positive Values Scale (PVS) as part of a school climate survey. Results showed that for the PVS, a two-correlated factor model at Level 1 and a one-factor model at Level 2 best fit the data. Implications and guidance for applied researchers are discussed.
Descriptors: Hierarchical Linear Modeling, Factor Analysis, Factor Structure, Measures (Individuals), Middle School Students, Educational Environment, Values, Student Surveys, Psychometrics, Data, Grade 7, Grade 8
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Publication Type: Journal Articles; Reports - Research
Education Level: Middle Schools; Secondary Education; Junior High Schools; Grade 7; Elementary Education; Grade 8
Sponsor: US Department of Justice, Office of Juvenile Justice and Delinquency Prevention
Authoring Institution: N/A
Identifiers - Location: Virginia
Grant or Contract Numbers: 2012JFFX0062