Discrete-Time Discrete-State Latent Markov Models with Time-Constant and Time-Varying Covariates
- 1 June 1999
- journal article
- Published by American Educational Research Association (AERA) in Journal of Educational and Behavioral Statistics
- Vol. 24 (2) , 179-207
- https://doi.org/10.3102/10769986024002179
Abstract
Discrete-time discrete-state Markov chain models can be used to describe individual change in categorical variables. But when the observed states are subject to measurement error, the observed transitions between two points in time will be partially spurious. Latent Markov models make it possible to separate true change from measurement error The standard latent Markov model is, however, rather limited when the aim is to explain individual differences in the probability of occupying a particular state at a particular point in time. This paper presents a flexible logit regression approach which allows to regress the latent states occupied at the various points in time on both time- constant and time-varying covariates. The regression approach combines features of causal log-linear models and latent class models with explanatory variables. In an application pupils' interest in physics at different points in time is explained by the time-constant covariate sex and the time-varying covariate physics grade. Results of both the complete and partially observed data are presented.Keywords
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This publication has 32 references indexed in Scilit:
- Latent Change in Recurrent Choice DataPsychometrika, 1996
- Goodness-of-Fit Testing for Latent Class ModelsMultivariate Behavioral Research, 1993
- Linear Logistic Latent Class Analysis for Polytomous DataJournal of the American Statistical Association, 1992
- Latent Class Models for Stage-Sequential Dynamic Latent VariablesMultivariate Behavioral Research, 1992
- Concomitant-Variable Latent-Class ModelsJournal of the American Statistical Association, 1988
- Regression Analysis for Categorical Variables with Outcome Subject to Nonignorable NonresponseJournal of the American Statistical Association, 1988
- Causal Models for Patterns of NonresponseJournal of the American Statistical Association, 1986
- Intrinsic Motivation and Self-Determination in Human BehaviorPublished by Springer Nature ,1985
- Latent Structure Analysis of a Set of Multidimensional Contingency TablesJournal of the American Statistical Association, 1984
- Maximum Likelihood Estimation and Model Selection in Contingency Tables with Missing DataJournal of the American Statistical Association, 1982