My answer to your question is "none of the above". Better to appreciate my answer, I recommend that you consult the special section (on the topic of dealing with missing data) in volume 6, issue 4 of Psychological Methods (2001).
Karl W. -----Original Message----- We are doing a regression, however there a plenty of missing values, which cannot be dropped, so somehow have to be imputed. Ther are some options, a) Replace the problem regressor by a dummy variable b) Replace the missing by median (it is demographic data) c) Replace the missing data by the trimmed/winsorized mean. d) Replace by mode Which is better altenative?? . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
