Thanks for quick responses.

My dataset consists of 213 independent variables (disease related costs) and
the depedent variable is the total medical + pharmacy cost of the member.

As you had suggested, I tried to use hier.part function in R, but the
current implementation does not seem to allow more than 13 independent
variables at a time. Meanwhile, I am also trying to get access to the paper
"Variable importance by partitioning R^2".

I am currently using t-values from multiple regression to perform ranking of
variables. But the result does not seem to be satisfactory.

With regards,
Rupendra Chulyadyo
Institute of Engineering,
Tribhuvan University,
Nepal


On 1/17/07, Simon Blomberg <blomsp@ozemail.com.au> wrote:
>
> Before you do that, you might try reading this paper:
>
> Bring, J. 1995. Variable importance by partitioning R^2. Quality and
> Quantity 29:173-189.
>
> Cheers,
>
> Simon.
>
> Andrew Robinson wrote:
> > Rupendra,
> >
> > depending on the nature of your data (which you haven't mentioned),
> > you might try hierarchical partitioning, as found in the hier.part
> > package on CRAN.
> >
> > Cheers
> >
> > Andrew
> >
> > On Wed, Jan 17, 2007 at 11:07:18AM +0545, Rupendra Chulyadyo wrote:
> >> Hello all,
> >>
> >> I want to assign relative score to the predictor variables on the basis
> of
> >> its influence on the dependent variable. But I could not find any
> standard
> >> statistical approach appropriate for this purpose.
> >> Please suggest the possible approaches.
> >>
> >> Thanks in advance,
> >>
> >> Rupendra Chulyadyo
> >> Institute of Engineering,
> >> Tribhuvan University,
> >> Nepal
> >>
> >>      [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> 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
> >> and provide commented, minimal, self-contained, reproducible code.
> >
>
>
> --
> Simon Blomberg, B.Sc.(Hons.), Ph.D, M.App.Stat.
> Centre for Resource and Environmental Studies
> The Australian National University
> Canberra ACT 0200
> Australia
> T: +61 2 6125 7800 email: Simon.Blomberg_at_anu.edu.au
> F: +61 2 6125 0757
> CRICOS Provider # 00120C
>
> The combination of some data and an aching desire for
> an answer does not ensure that a reasonable answer
> can be extracted from a given body of data.
> - John Tukey.
>

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