Hello, there are lots of suggestions for the minimum data for regression models, i.e.
1) 1 var. for every 10 observations. 2) Variables can be added until Adjusted R-square deviates substantially Unadjusted R-square. 3) With relatively large samples (n=100), a variable can be added if is correlation with other variables is no larger than about 0.80 or 0.85. My question is, whether the 1) suggestion should be condsidered with a stepwise regression, too. That means when I do a stepwise regression and get i.e. 20 variables are 200 obeserved values sufficient for prediction or is it important to have as much observations as there are "possible" variables before the use of the stepwise method. Thanks a lot, Bastian . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
