(since we're all top-posting here), I'll first say what you already know, that this analytic approach will not yield much in the way of meaningful information. Hopefully, the editors will recognize this, too, at the time of review.
If I HAD to come up with a solution of how to manage interactions in this situations, I would probably use the approach of orthogonalizing the interaction terms with respect to their main effects components. I belive this is described in Draper and Smith. Donald Burril also used to have a nice tutorial on this at the Minitab site but it seems to be gone now. Basically, you regress the product term on the main effects components and use the residuals as the interaction term. The residuals are centered and orthogonal to the main effects, meaning that it isn't neccesary to have the main effects terms in the model. All this said, I still would try to encourage this person to refine his hypotheses and/or collect more data, and then prespecify the model as completely as possible. He'll get a result, but he won't know whether it's nonsense or not. Mike Babyak Scheltema, Karen <[EMAIL PROTECTED]> wrote: : 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? : -----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 me ssage 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/ . : ================================================================= -- _________________________________________________________________ Michael A. Babyak, PhD (919) 684-8843 (Voice) Box 3119 (919) 684-8629 (Fax) Department of Psychiatry Duke University Medical Center [EMAIL PROTECTED] Durham, NC 27710 _________________________________________________________________ In Flumine Stercoris Noli Undas Facere _________________________________________________________________ . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
