A one-day Mplus short course on Bayesian analysis will be held on May 24 at the University of Connecticut. The host for the short course is the Educational Psychology Department, Neag School of Education. This short course will be held prior to the Modern Modeling Methods Conference, to be held at UConn on May 25-26, 2011.
Bayesian analysis has many desirable features and advantages. It performs better than maximum-likelihood analysis in smaller samples, with fewer clusters in multilevel analysis, and for models with many factors and/or random effects. Bayesian analysis also has the advantage over maximum-likelihood analysis that substantive hypotheses can be formulated in a more flexible way using informative priors as shown in:
http://www.statmodel.com/download/BSEMv4REVISED.pdf
Bayesian analysis is also an effective way to handle missing data using multiple imputation. Bayesian analysis has been incorporated into the general latent variable modeling framework of Mplus. This makes it easier than ever to carry out Bayesian analysis in practice for a wide variety of models.
The one-day course is similar to Topic 9 in the 9-topic Mplus course sequence. See:
http://www.statmodel.com/coursesequence.shtml
For videos and handouts from past courses, see:
http://www.statmodel.com/course_materials.shtml
Bengt Muthén, Professor Emeritus, UCLA
For each topic, issues of model specification, identification, estimation, testing, and model modification will be discussed. Several examples will be examined. Modeling strategies will be presented. Mplus input setups will be provided and Mplus output will be used for interpretation of analysis results. The presentations will be in lecture form with no need for laptop computing.
Desirable background includes topics 1-8 of the Mplus short courses (see www.statmodel.com), covering structural equation modeling, growth modeling, mixture modeling, and multilevel modeling or some experience with the MPLUS software program. Web movies of past short courses can be watched for free.