Two-Step Estimation of Models Between Latent Classes and External Variables

Zsuzsa Bakk () and Jouni Kuha
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Zsuzsa Bakk: Leiden University
Jouni Kuha: London School of Economics and Political Science

Psychometrika, 2018, vol. 83, issue 4, No 6, 892 pages

Abstract: Abstract We consider models which combine latent class measurement models for categorical latent variables with structural regression models for the relationships between the latent classes and observed explanatory and response variables. We propose a two-step method of estimating such models. In its first step, the measurement model is estimated alone, and in the second step the parameters of this measurement model are held fixed when the structural model is estimated. Simulation studies and applied examples suggest that the two-step method is an attractive alternative to existing one-step and three-step methods. We derive estimated standard errors for the two-step estimates of the structural model which account for the uncertainty from both steps of the estimation, and show how the method can be implemented in existing software for latent variable modelling.

Keywords: latent variables; mixture models; structural equation models; pseudo-maximum likelihood estimation (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (12)

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DOI: 10.1007/s11336-017-9592-7

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