Getting Categorical CFA fit statistics with MPLUS

CFA is a way to establish the dimensionalities of your data. For instance, unidimensionality and local independence are the assumptions of (unidimensional) IRT.

Just learned it today...

The default ML estimation does not provide model fit statistics for MPlus if you are running Categorical CFA. However if we change the method of estimation to wlsmv, it will spit out CFI, TLI and RMSEA in the output.

ANALYSIS: estimator=wlsmv;

Following are the links:

1. http://www.statmodel.com/discussion/messages/9/1881.html?1166123658
2. http://www.indiana.edu/~statmath/stat/all/cfa/cfa14.html

The Theory and Practice of Item Response Theory By R. J. de Ayala

This is a nice book for IRT... explains a lot of stuffs pretty well in plain English... It is with information provided in this book did I figure out how to use item response pattern as the ID for bilog-MG output

The Theory and Practice of Item Response Theory By R. J. de Ayala

Chapter 10 IRT Applications: DIF, CAT and SCALE ANALYSIS (DIF only)

Please find my notes for the DIF section at the following URL:

This chapter is in the book "Item Response Theory for Psychologists" by Embretson & Reise (2000)

http://sites.google.com/site/yaowensite/math-statistics-and-measurement-resources/item-response-theory/Chapter10IRTApplications.docx?attredirects=0