[R] Stepwise model comparisons for mlogit

[Joshua Wiley]

Hi Louis,

It seems to me that the easiest way to accomplish what you want is to
just define an extractAIC method for objects of class "mlogit".  I am
not familiar with multinomial logistic models, so this may not be
correct (I am especially uncertain about the degrees of freedom I
used), but it should get you close.  You just need to edit the formula
to be correct and then step(), etc. should all work.

extractAIC.mlogit <- function (fit, scale = 0, k = 2, ...) {
    n <- length(fit$residuals)
    edf <- length(fit$coefficients)
    aic <- (-2 * fit$logLik) + k + edf
    c(edf, aic + (k - 2) * edf)
}

You can also look at:

require(MASS)
?stepAIC

Hope this helps,

Josh



On Mon, Jun 20, 2011 at 12:36 PM, Merlin, Louis <lmerlin at email.unc.edu> wrote:
> I am trying to perform a backwards stepwise variable selection with an mlogit model.  The usual functions, step(), drop1(), and dropterm() do not work for mlogit models.
>
>
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> Update() works but I am only able to use it manually, i.e. I have to type in each variable I wish to remove by hand on a separate line.
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> My goal is to write some code that will systematically remove a certain set of variables one at a time and compare the AIC of each alternative model.
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> i.e.:
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> famodel1.mn <- mlogit(Chosen ~ 0 + q23_wt + park_avg + walk_avg + aesth_avg + Length + ln_ps, data = data.mn)
>
> I wish to remove each of "q23_wt", "park_avg", "walk_avg" and "aesth_avg" one at a time from the above model, without having to type each version manually.
>
>
>
> Louis Merlin
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>
>
>
>
> ________________________________
>
> Mr. Louis Merlin, AICP
>
> Doctoral Student
>
> UNC CH Department of City and Regional Planning
>
>        [[alternative HTML version deleted]]

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-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/