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XWITH for Bayes. This avoids slow computations using ML when many XWITH terms are included. ML bootstrapping to get non-symmetric confidence intervals is not needed with Bayes because such intervals are part of its estimation.
Latent variable decomposition (latent variable centering) of predictors with random slopes for DSEM, RDSEM, and other TYPE=TWOLEVEL models using the Bayes estimator (Asparouhov & Muthén, 2018b, (Download scripts)) as shown in Example 9.1 for a random intercept model in the Mplus Version 8 User’s Guide
(RDSEM)
STANDARDIZED, RESIDUAL, AND TECH4 for RDSEM
Speed improvements for Bayes two-level analysis especially with random variances
SUM and MEAN options for the MODEL CONSTRAINT command. See the DEFINE command for examples
New Mplus Technical Note: Random starting values and multistage optimization.
Pause During Mplus Analysis
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