I once asked Don Rubin if he was miffed that some of his best ideas, including the characterization of missing-data processes (“missing completely at random,” “missing at random,” etc.) and multiple imputation are commonly mentioned without citing him at all. He said that he actually considers it a compliment that these ideas are so accepted that they need no citation. Along those lines, he’d probably be happy to know that we’re now getting unsolicited emails of the following sort:

Dear Colleague:

On Nov. 10-11 in New York City, I [unsolicited emailer] will be presenting my 2-day course on Missing Data. This course provides an in-depth look at modern methods for handling missing data, with particular emphasis on maximum likelihood and multiple imputation. These methods have been demonstrated to be markedly superior to conventional methods like listwise deletion or single imputation, while at the same time resting on less stringent assumptions.

While the course is applications oriented, I also explain the conceptual underpinnings of these new methods in some detail. Maximum likelihood is illustrated with two programs, Amos and LEM. Multiple imputation is demonstrated with two SAS procedures (MI and MIANALYZE) and two Stata commands (ICE and MICOMBINE).

The course will be held at the . . . Hotel . . . Guest rooms are available at the hotel at a special rate.

You can get more detailed information at . . .

If you’d prefer not to get announcements like this in the future, please reply to this e-mail and ask to removed from the list.