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Maximum Likelihood Estimation of Multilevel Structural Equation Models with Random Slopes for Latent Covariates
1Division of Interdisciplinary Studies, School of Behavioral Health, Loma Linda University, 11065 Campus St., Loma Linda, CA, 92350, USA. nrockwood@llu.edu.
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.
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