Multilevel Heterogeneous Factor Analysis and Application to Ecological Momentary Assessment

Junhao Pan, Edward Haksing Ip () and Laurette Dubé
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Junhao Pan: Sun Yat-sen University
Edward Haksing Ip: Wake Forest School of Medicine
Laurette Dubé: McGill University

Psychometrika, 2020, vol. 85, issue 1, No 6, 75-100

Abstract: 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 analysis; ecological momentary assessment; residual covariance matrix; random effects; MCMC methods (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11336-019-09691-4

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