[R] Stepwise logistic model selection using Cp and BIC criteria

[Dimitris Rizopoulos]

For model selection using BIC you can have a look at stepAIC() from 
package MASS and boot.stepAIC() from package bootStepAIC. For 
instance,

library(bootStepAIC)

boot.stepAIC(glmFit1, data, B = 50, k = log(nrow(n)))

where `glmFit1' is the object represinting the fitted model, `data' 
the data.frame containing the variables for the analysis, `B' the 
number of bootstrap replicates, and `k' is the multiple of the number 
of degrees of freedom used for the penalty, which when equal to log(n) 
is the BIC.

By default boot.stepAIC() returns as well the results of stepAIC().

I hope it helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm


----- Original Message ----- 
From: "Tirthadeep" <sabya231 at gmail.com>
To: <r-help at stat.math.ethz.ch>
Sent: Monday, September 17, 2007 7:36 AM
Subject: [R] Stepwise logistic model selection using Cp and BIC 
criteria


>
> Hi,
>
> Is there any package for logistic model selection using BIC and 
> Mallow's Cp
> statistic? If not, then kindly suggest me some ways to deal with 
> these
> problems.
>
> Thanks.
> -- 
> View this message in context: 
> http://www.nabble.com/Stepwise-logistic-model-selection-using-Cp-and-BIC-criteria-tf4464430.html#a12729613
> Sent from the R help mailing list archive at Nabble.com.
>
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