Original paper
7. Four Useful Finite Mixture Models for Regression Analyses of Panel Data with a Categorical Dependent Variable
Abstract
This paper describes and contrasts two useful ways to employ a latent class variable as a mixture variable in regression analyses of panel data with a categorical dependent variable. One way is to model unobserved heterogeneity in the trajectory, or change in the distribution, of the dependent variable. Two models that accomplish this are the latent trajectory model and latent growth curve model for a categorical dependent variable having...
Paper Details
Title
7. Four Useful Finite Mixture Models for Regression Analyses of Panel Data with a Categorical Dependent Variable
Published Date
Jun 28, 2008
Journal
Volume
38
Issue
1
Pages
283 - 328
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History