Muthén & Muthén, Mplus Home Page
2024年9月17日 · Instats has a large library of On-Demand, self-paced Mplus workshops available including two free 1-hour introductory Mplus courses. Quantfish is offering a variety of On-Demand Mplus courses including two free Mplus mini-courses .
Mplus Demo Version
Mplus Version 8.11 Demo is now available for download at no cost for Windows operating systems, Mac OS X, and Linux operating systems. The demo version contains all of the capabilities of the regular version of Mplus.
Mplus - General Description
Mplus is a statistical modeling program that provides researchers with a flexible tool to analyze their data. Mplus offers researchers a wide choice of models, estimators, and algorithms in a program that has an easy-to-use interface and graphical displays of data and analysis results.
Building Your Mplus Skills | Mplus Seminars - OARC Stats
This approach consists of a few steps: deciding the appropriate models for the study; deciding if switching to Mplus is necessary; preparing the data structure for Mplus using a familiar software package; and moving to Mplus and performing the analyses.
MPlus Notes - 10 Multilevel Models - Social Science Computing ...
Multilevel Models. The MPlus language has options that allow you to work with mulilevel data in long form, in the style of mixed modeling software in contrast to the wide (or multivariate) form, typically used in SEM approaches to growth modeling and repeated measures.
Mplus: how to get started - Rens van de Schoot
Welcome on the ‘How to Get Started’ page of of Mplus. We developed a set of tutorials: How to run a simple (frequentist) regression analysis; We also have tutorials on how to run the same models, but in a Bayesian way: Bayesian regression with default and user-specified priors
Mplus 8-4: a software review | Journal of Marketing Analytics
2020年7月28日 · Mplus is a powerful statistical program that performs robust estimations of chi-square tests for model fit using a likelihood approach in which means and variances are adjusted. Standard errors are computed using bootstrapping, and non-normality of outcomes is taken into consideration (Muthén and Muthén 2017 ).