Multilevel Factor Models for Ordinal Variables

Leonardo Grilli · Carla Rampichini

69 citations0/0 files storedStructural Equation Modeling A Multidisciplinary Journal

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Psychometric Methodologies and Testing Statistical Methods and Bayesian Inference Mental Health Research Topics

Abstract

This article tackles several issues involved in specifying, fitting, and interpreting the results of multilevel factor models for ordinal variables. First, the problem of model specification and identification is addressed, outlining parameter interpretation. Special attention is devoted to the consequences on interpretation stemming from the usual choice of not decomposing the specificities into hierarchical components. Then a general strategy of analysis is outlined, highlighting the role of the exploratory steps. The theoretical topics are illustrated through an application to graduates' job satisfaction, where estimation is based on maximum likelihood via an Expectation-Maximization algorithm with adaptive quadrature.

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References

1984A General Structural Equation Model with Dichotomous, Ordered Categorical, and Continuous Latent Variable Indicators 1985A comparison of some methodologies for the factor analysis of non‐normal Likert variables 2002Multilevel Statistical Models 1989Latent Variable Modeling in Heterogeneous Populations 2005Contemporary psychometrics : a festschrift for Roderick P. McDonald 2001Factor Analysis of Ordinal Variables: A Comparison of Three Approaches 2003A nonlinear mixed model framework for item response theory.1995Technical Aspects of Muthén's Liscomp Approach to Estimation of Latent Variable Relations with a Comprehensive Measurement Model

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