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Mixed-Effects Logistic Regression Models for Indirectly Observed Discrete Outcome Variables
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Vermunt, Jeroen K. – Multivariate Behavioral Research, 2005
A well-established approach to modeling clustered data introduces random effects in the model of interest. Mixed-effects logistic regression models can be used to predict discrete outcome variables when observations are correlated. An extension of the mixed-effects logistic regression model is presented in which the dependent variable is a latent…
Descriptors: Predictor Variables, Correlation, Maximum Likelihood Statistics, Error of Measurement