On April 25-26, 2003, I will be offering a two-day course on Missing Data in Philadelphia.
After reviewing the strengths and weaknesses of conventional methods, the course will focus two newer methods, maximum likelihood and multiple imputation, that have much better statistical properties. These new methods have been around for at least a decade, but have only become practical in the last few years with the introduction of widely available and user friendly software. What's remarkable is that these methods depend on less demanding assumptions than those required for conventional methods. At present, maximum likelihood is best suited for linear models or log-linear models for contingency tables. Multiple imputation, on the other hand, can be used for virtually any statistical problem. Multiple imputation will be illustrated with the new MI procedure in SAS. Maximum likelihood will be implemented with structural equation modeling software (either Amos or LISREL). The text for the course will be my "Missing Data" published by Sage in 2001. For complete details, go to www.ssc.upenn.edu/~allison . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
