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Multilevel Heterogeneous Factor Analysis and Application to Ecological Momentary Assessment

Published online by Cambridge University Press:  01 January 2025

Junhao Pan,
Edward Haksing IpOpen the ORCID record for Edward Haksing Ip[Opens in a new window] and
Laurette Dubé
Junhao Pan
Affiliation:
Sun Yat-sen University
Edward Haksing Ip*
Affiliation:
Wake Forest School of Medicine
Laurette Dubé
Affiliation:
McGill University
*
Correspondence should be made to Edward Haksing Ip, Wake Forest School of Medicine, Winston-Salem, USA. Email: eip@wakehealth.edu URL: https://www.phs.wakehealth.edu/public/profile.cfm?staffid=57C5A0EA-1FF4-425F-BFE1-86EFB3A3CF72
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Abstract

Ansari et al. (Psychometrika 67:49–77, 2002) applied a multilevel heterogeneous model for confirmatory factor analysis to repeated measurements on individuals. While the mean and factor loadings in this model vary across individuals, its factor structure is invariant. Allowing the individual-level residuals to be correlated is an important means to alleviate the restriction imposed by configural invariance. We relax the diagonality assumption of residual covariance matrix and estimate it using a formal Bayesian Lasso method. The approach improves goodness of fit and avoids ad hoc one-at-a-time manipulation of entries in the covariance matrix via modification indexes. We illustrate the approach using simulation studies and real data from an ecological momentary assessment.

Keywords

confirmatory factor analysisecological momentary assessmentresidual covariance matrixrandom effectsMCMC methods

Information

Type
Theory and Methods
Information
Psychometrika , Volume 85 , Issue 1 , March 2020, pp. 75 - 100
Copyright
Copyright © 2019 The Psychometric Society

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