Mplus
Thursday
October 10, 2024
HOME ORDER CONTACT US CUSTOMER LOGIN MPLUS DISCUSSION
Mplus
Mplus at a Glance
General Description
Mplus Programs
Pricing
Version History
System Requirements
Platforms
Mplus Demo Version
Training
Mplus Web Talks
Short Courses
Short Course Videos
and Handouts
Web Training
Mplus YouTube Channel
Documentation
Mplus User's Guide
Mplus Diagrammer
Technical Appendices
Mplus Web Notes
FAQ
User's Guide Examples
Mplus Book
Mplus Book Examples
Mplus Book Errata
Analyses/Research
Mplus Examples
Papers
References
Special Mplus Topics
Bayesian SEM (BSEM)
Complex Survey Data
DSEM – MultiLevel Time Series Analysis
Exploratory SEM (ESEM)
Genetics
IRT
Measurement Invariance
and Alignment
Mediation Analysis
Missing Data
Mixture Modeling
Multilevel Modeling
Randomized Trials
RI-CLPM
RI-LTA
Structural Equation Modeling
Survival Analysis
How-To
Using Mplus via R -
MplusAutomation
Mplus plotting using R
H5 results
Chi-Square Difference
Test for MLM and MLR
Power Calculation
Monte Carlo Utility
Search
 
Mplus Website Updates
Mplus Privacy Policy
VPAT/508 Compliance

Chapter 10: Multilevel Mixture Modeling

Download all Chapter 10 examples

Example View output Download input Download data View Monte Carlo output Download Monte Carlo input
10.1: Two-level mixture regression for a continuous dependent variable ex10.1 ex10.1.inp ex10.1.dat mcex10.1 mcex10.1.inp
10.2: Two-level mixture regression for a continuous dependent variable with a between-level categorical latent variable ex10.2 ex10.2.inp ex10.2.dat mcex10.2 mcex10.2.inp
10.2: Two-level mixture regression for a continuous dependent variable with a between-level categorical latent variable (alternate) ex10.2alt ex10.2alt.inp ex10.2.dat none none
10.3: Two-level mixture regression for a continuous dependent variable with between-level categorical latent class indicators for a between-level categorical latent variable ex10.3 ex10.3.inp ex10.3.dat mcex10.3 mcex10.3.inp
10.4: Two-level CFA mixture model with continuous factor indicators ex10.4 ex10.4.inp ex10.4.dat mcex10.4 mcex10.4.inp
10.5: Two-level IRT mixture analysis with binary factor indicators and a between-level categorical latent variable ex10.5 ex10.5.inp ex10.5.dat mcex10.5 mcex10.5.inp
10.6: Two-level LCA with categorical latent class indicators with covariates ex10.6 ex10.6.inp ex10.6.dat mcex10.6 mcex10.6.inp
10.7: Two-level LCA with categorical latent class indicators and a between-level categorical latent variable ex10.7 ex10.7.inp ex10.7.dat mcex10.7 mcex10.7.inp
10.8: Two-level growth model for a continuous outcome (three-level analysis) with a between-level categorical latent variable ex10.8 ex10.8.inp ex10.8.dat mcex10.8 mcex10.8.inp
10.8: Two-level growth model for a continuous outcome (three-level analysis) with a between-level categorical latent variable (alternate) ex10.8alt ex10.8alt.inp ex10.8.dat none none
10.9: Two-level GMM for a continuous outcome (three-level analysis) ex10.9 ex10.9.inp ex10.9.dat mcex10.9 mcex10.9.inp
10.10: Two-level GMM for a continuous outcome (three-level analysis) with a between-level categorical latent variable ex10.10 ex10.10.inp ex10.10.dat mcex10.10 mcex10.10.inp
10.11: Two-level LCGA for a three-category outcome ex10.11 ex10.11.inp ex10.11.dat mcex10.11 mcex10.11.inp
10.12: Two-level LTA with a covariate ex10.12 ex10.12.inp ex10.12.dat mcex10.12 mcex10.12.inp
10.13: Two-level LTA with a covariate and a between-level categorical latent variable ex10.13 ex10.13.inp ex10.13.dat mcex10.13 mcex10.13.inp

Back to User's Guide Examples