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Bayes estimation with censored variables for single-level SEM, mixture models, models with latent variable interactions, RSEM, and DSEM.
TECH10 standardized residuals for response patterns and univariate and bivariate frequency tables (Asparouhov & Muthen, 2022c) for Bayes with two-part ordinal models and Bayes with PREDICTOR=OBSERVED as used in Mplus Web Talk 4, Part 2.
The measurements are typically closely spaced in time. In Mplus, both N=1 models and a variety of two-level and cross-classified time series models can be estimated. These include univariate autoregressive, regression, cross-lagged, confirmatory factor analysis,
Three new models have been added for categorical dependent variables: the Three-parameter Logistic Regression Model with a guessing parameter (3PL), the Four-parameter Logistic Regression Model with lower (guessing) and upper asymptote parameters (4PL), and the Partial Credit Model (PCM).
Time Series Analysis
Time series analysis is used to analyze intensive longitudinal data such as those obtained with ecological momentary assessments, experience sampling methods, daily diary methods, and ambulatory assessments. Such data typically have a large number of time points, for example, twenty to two hundred.
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