Maximum Likelihood Estimation of Multilevel Structural Equation Models with Random Slopes for Latent Covariates

Nicholas J. Rockwood ()
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Nicholas J. Rockwood: Loma Linda University

Psychometrika, 2020, vol. 85, issue 2, No 2, 275-300

Abstract: Abstract A maximum likelihood estimation routine for two-level structural equation models with random slopes for latent covariates is presented. Because the likelihood function does not typically have a closed-form solution, numerical integration over the random effects is required. The routine relies upon a method proposed by du Toit and Cudeck (Psychometrika 74(1):65–82, 2009) for reformulating the likelihood function so that an often large subset of the random effects can be integrated analytically, reducing the computational burden of high-dimensional numerical integration. The method is demonstrated and assessed using a small-scale simulation study and an empirical example.

Keywords: multilevel SEM; random effects; random slopes; maximum likelihood estimation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11336-020-09702-9

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