September 02, 2010
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| Mplus Website Updates |
Last updated: August 22, 2010
Latest News
Mplus Version 6 is now available.
The major new feature in Mplus Version 6 is Bayesian analysis using MCMC. This includes multiple imputation for missing data as well as plausible values for latent variables. Other additions include replicate weights for complex survey data, survival analysis models and plots, convenience features for modeling with missing data, and several new general features. Click here for more information.
Mplus Version 6 is available at no cost to anyone who purchased Mplus within the last year and to those with a current upgrade and support contract. To download the 32- or 64-bit version of Mplus Version 6 go to the website under Support - Mplus Updates.
Mplus Demo Version
The Mplus Demo version is available for download at no cost. Click here to download the demo. The demo version contains all of the capabilities of the regular version of Mplus and is only limited by the number of observed variables that can be used in an analysis.
Student Pricing for Mplus Version 6
Special student pricing is available for Mplus. The student version of the program is identical to the regular version. Click here for more information.
Mplus Version 6 User's Guide and Examples
Click here for the Mplus Version 6 User's Guide and to download the input, output, and data for the Mplus User's Guide examples.
Mplus Web Training and Handouts
Videos and handouts for the 8 topics of the Mplus Short Courses are now available for viewing on the web. Other Mplus web training includes web talks, a seminar series, a one-day overview course, a two-day course, and a 20-lecture course on Mplus analyses.
Papers Using Special Mplus Features
Click here to find papers ordered by topic and by date.
Mplus Web Notes
Mplus Web Notes is a vehicle for presenting information on Mplus analysis techniques. Click here to go to Mplus Web Notes.
Mplus Complex Survey Data Project
Mplus has an ongoing research project on complex survey analysis for multivariate models. Papers from this project will be posted as the research progresses. Click here for papers from this project.