Mplus
Thursday
December 03, 2020
HOME ORDER CONTACT US CUSTOMER LOGIN MPLUS DISCUSSION
Mplus
Mplus at a Glance
General Description
Mplus Programs
Pricing
Version History
System Requirements
Platforms
FAQ
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
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
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
Mplus plotting using R
Chi-Square Difference
Test for MLM and MLR
Power Calculation
Monte Carlo Utility
Search
 
Mplus Website Updates
Mplus Privacy Policy

Randomized Trials

Mplus provides new methods for the analysis of data from randomized trials (clinical trials, randomized preventive interventions):

Complier-average causal effect (CACE) modeling--assessing treatment effects among compliers in the treatment group as compared to potential compliers in the control group. Mplus setup for CACE modeling. Mplus Examples.

Growth mixture modeling--allowing treatment effects to vary across latent trajectory classes and among individuals within classes. View setup for growth mixture modeling.

For more information, visit our General Description page.

For more papers see our Randomized Trials paper topics.