I know about the perils of stepwise, and I agree with you that it is a less than desirable procedure. This researcher, however, is not as convinced as I am about not doing stepwise. Sigh. He has more variables than would comfortably fit a 5-1 case to variable ratio for a forced entry regression, which is why he was hoping stepwise would help him narrow his model. Any suggestions I can give him, short of telling him to scrap everything?
Karen Scheltema, M.A, M.S. Senior Statistician HealthEast Research and Education Department, Midway Campus 1700 University Ave W St. Paul, MN 55104 Ph: (651) 232-5212 fax: (651) 641-0683 mailto:[EMAIL PROTECTED] -----Original Message----- From: Paul R Swank [mailto:[EMAIL PROTECTED] Sent: Wednesday, May 28, 2003 8:26 AM To: Scheltema, Karen; Ed Stat (E-mail) Subject: RE: VIF for dichotmous variable This is another good illustration why one should not use automatic procedures for research. The problem of interactions in stepwise procedures is that the compute doesn't know it is an interaction and that you can't drop the main effects while the interaction is strill in the model. If the interaction is significant then the main ewffects that make up the interaction must stay in the model. By the way, there is backward selection, forward selection, and stepwise selection (plus several other more esoteric procedures) but I, for one, have never heard of backwward stepwise. Paul R. Swank, Ph.D. Professor, Developmental Pediatrics Medical School UT Health Science Center at Houston -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Scheltema, Karen Sent: Tuesday, May 27, 2003 4:08 PM To: [EMAIL PROTECTED] Subject: VIF for dichotmous variable I have a colleague who has run a backwards stepwise linear regression. A couple of the variables are problematic. One is a dichotomous variable that indicates trying to get pregnant (y/n) and the other is a continuous variable that is a scale score. It is believed that the two interact with each other. In the initial run, the scale was centered, but the dichotomous variable was not. This yielded high VIFs (>100) in the initial regression equation, but the scale dropped out by the latter stages of the stepwise regression. I suggested centering the dichotomous variable, as well, but this yielded VIFs>300 in the initial steps. Since this scale variables drops out later, can I just ignore this? Or, can someone suggest another solution to try? Karen Scheltema, M.A, M.S. Senior Statistician HealthEast Research and Education Department, Midway Campus 1700 University Ave W St. Paul, MN 55104 Ph: (651) 232-5212 fax: (651) 641-0683 mailto:[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]> The information included in this e-mail message, including any attachments, is intended only for the person or organization to which it is addressed. This e-mail message may contain information that is privileged or confidential. If you receive this e-mail message and are not the intended recipient or responsible for delivering the message to the intended recipient, you may not use, disseminate, distribute or copy the information included in this e-mail and any attachments. If you received this e-mail message by mistake, please reply by e-mail and destroy all copies of this message and any attachments. Thank you. The information included in this e-mail message, including any attachments, is intended only for the person or organization to which it is addressed. This e-mail message may contain information that is privileged or confidential. If you receive this e-mail message and are not the intended recipient or responsible for delivering the message to the intended recipient, you may not use, disseminate, distribute or copy the information included in this e-mail and any attachments. If you received this e-mail message by mistake, please reply by e-mail and destroy all copies of this message and any attachments. Thank you. . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
