R help - Feb 2007 - bootstrap

Hi,
I would like to evaluate the frequency of the variables within the best selected
model by AIC among a set of 12 competing models (I fit them with GLM) with a
bootstrap procedure  to get unbiased results. So I would ike to do the ranking
of the 12-model-set 10'000 times separately and calculate the frequency of
variables of the 10'000 best ranked models. I wrote a script doing the model
ranking (with some difficulty) for the pre-defined 12-model-set, that works. My
model results (one row per model) are stored in a dataframe called
"mydataframe". How can I implement my script simply into a bootstrap
and sum up the frequencies of variables of the 10'000 bootstraped results?
 
I am not so good in R and would appreciate any hint.
 
Regards
Lukas
 
 
??? 
Lukas Indermaur, PhD student 
eawag / Swiss Federal Institute of Aquatic Science and Technology 
ECO - Department of Aquatic Ecology
?berlandstrasse 133
CH-8600 D?bendorf
Switzerland
 
Phone: +41 (0) 71 220 38 25
Fax    : +41 (0) 44 823 53 15 
Email: lukas.indermaur at eawag.ch
www.lukasindermaur.ch

Indermaur Lukas wrote:
> Hi,
> I would like to evaluate the frequency of the variables within the best
selected model by AIC among a set of 12 competing models (I fit them with GLM)
with a bootstrap procedure  to get unbiased results. So I would ike to do the
ranking of the 12-model-set 10'000 times separately and calculate the
frequency of variables of the 10'000 best ranked models. I wrote a script
doing the model ranking (with some difficulty) for the pre-defined 12-model-set,
that works. My model results (one row per model) are stored in a dataframe
called "mydataframe". How can I implement my script simply into a
bootstrap and sum up the frequencies of variables of the 10'000 bootstraped
results?
>  
> I am not so good in R and would appreciate any hint.
>  
> Regards
> Lukas
I'm not entirely clear on your goals but the bootstrap selection 
frequency is mainly a replay of the significance of variables in the 
full model.  I don't see that it provides new information.  And 
selection frequency is marred by collinearity.

Frank
>  
>  
> ??? 
> Lukas Indermaur, PhD student 
> eawag / Swiss Federal Institute of Aquatic Science and Technology 
> ECO - Department of Aquatic Ecology
> ?berlandstrasse 133
> CH-8600 D?bendorf
> Switzerland
>  
> Phone: +41 (0) 71 220 38 25
> Fax    : +41 (0) 44 823 53 15 
> Email: lukas.indermaur at eawag.ch
> www.lukasindermaur.ch
> 
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-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University