I am hoping to get some advise on the following: I am looking for an automatic variable selection procedure to reduce the number of potential predictor variables (~ 50) in a multiple regression model. I would be interested to use the forward stepwise regression using the partial F test. I have looked into possible R-functions but could not find this particular approach. There is a function (stepAIC) that uses the Akaike criterion or Mallow's Cp criterion. In addition, the drop1 and add1 functions came closest to what I want but with them I cannot perform the required procedure. Do you have any ideas? Kind regards, Robin Smit -------------------------------------------- Business Unit TNO Automotive Environmental Studies & Testing PO Box 6033, 2600 JA Delft THE NETHERLANDS ph. +31 (0)15 269 7464 fax +31 (0)15 269 6874 robin.smit@tno.nl http://www.automotive.tno.nl/est <http://www.automotive.tno.nl/est> -------------------------------------------- This e-mail and its contents are subject to the DISCLAIMER at http://www.tno.nl/disclaimer/email.html [[alternative HTML version deleted]]
Frank E Harrell Jr
2005-Feb-24 12:15 UTC
[R] Forward Stepwise regression based on partial F test
Smit, Robin wrote:> I am hoping to get some advise on the following: > > I am looking for an automatic variable selection procedure to reduce the > number of potential predictor variables (~ 50) in a multiple regression > model. > > I would be interested to use the forward stepwise regression using the > partial F test. > I have looked into possible R-functions but could not find this > particular approach. > > There is a function (stepAIC) that uses the Akaike criterion or Mallow's > Cp criterion. > In addition, the drop1 and add1 functions came closest to what I want > but with them I cannot perform the required procedure. > Do you have any ideas? > > Kind regards, > Robin Smit > -------------------------------------------- > Business Unit TNO Automotive > Environmental Studies & Testing > PO Box 6033, 2600 JA Delft > THE NETHERLANDSRobin, If you are looking for a method that does not offer the best predictive accuracy and that violates every aspect of statistical inference, you are on the right track. See http://www.stata.com/support/faqs/stat/stepwise.html for details. -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University
Robin, You may see leaps() (package leaps). It deals with all subsets regression considering several chosen criteria. beste Regards, Alex models ---------- Início da mensagem original ----------- De: r-help-bounces@stat.math.ethz.ch Para: "Smit, Robin" robin.smit@tno.nl Cc: r-help@stat.math.ethz.ch Data: Thu, 24 Feb 2005 07:15:03 -0500 Assunto: Re: [R] Forward Stepwise regression based on partial F test> Smit, Robin wrote: > > I am hoping to get some advise on the following: > > > > I am looking for an automatic variable selection procedure to reduce the > > number of potential predictor variables (~ 50) in a multiple regression > > model. > > > > I would be interested to use the forward stepwise regression using the > > partial F test. > > I have looked into possible R-functions but could not find this > > particular approach. > > > > There is a function (stepAIC) that uses the Akaike criterion or Mallow's > > Cp criterion. > > In addition, the drop1 and add1 functions came closest to what I want > > but with them I cannot perform the required procedure. > > Do you have any ideas? > > > > Kind regards, > > Robin Smit > > -------------------------------------------- > > Business Unit TNO Automotive > > Environmental Studies & Testing > > PO Box 6033, 2600 JA Delft > > THE NETHERLANDS > > Robin, > > If you are looking for a method that does not offer the best predictive > accuracy and that violates every aspect of statistical inference, you > are on the right track. See > http://www.stata.com/support/faqs/stat/stepwise.html for details. > > -- > Frank E Harrell Jr Professor and Chair School of Medicine > Department of Biostatistics Vanderbilt University > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html >__________________________________________________________________________ AntiPop-up UOL - É grátis! [[alternative HTML version deleted]]