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Time series plots (sample values, ACF, PACF, estimated factor scores)
Other new features
Two-level modeling with random variances (User’s Guide ex 9.28, 9.29)
Two-level random autocorrelation modeling
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,
Automatic checking of whether two structural equation models are nested or equivalent (Bentler & Satorra. 2010) implemented and expanded to multiple group models and the weighted least squares estimators (Asparouhov & Muthén, 2018c, (Download scripts))
Expanded and modified SRMR (Asparouhov & Muthén, 2018d)
Bivariate residual tests and factor score standard errors for the weighted least squares estimators
Cluster-specific plots for TWOLEVEL
Expanded odds ratio output
Standard errors for correlations with TYPE=BASIC using the H1SE option of the OUTPUT command
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