R help - Apr 2009 - automatic exploration of all possible loglinear models?

Is there a way to automate fitting and assessing loglinear models for
several nominal variables . . . something akin to step or drop1 or add1
for linear or logistic regression?

Thanks.

--Chris
-- 
Christopher W. Ryan, MD
SUNY Upstate Medical University Clinical Campus at Binghamton
40 Arch Street, Johnson City, NY  13790
cryanatbinghamtondotedu

"If you want to build a ship, don't drum up the men to gather wood,
divide the work and give orders. Instead, teach them to yearn for the
vast and endless sea."  [Antoine de St. Exupery]

Christopher W. Ryan <cryan <at> binghamton.edu> writes:
> 
> Is there a way to automate fitting and assessing loglinear models for
> several nominal variables . . . something akin to step or drop1 or add1
> for linear or logistic regression?
Not strictly for loglinear, but glm works with stepAIC. Make sure that 
in the field you are working this approach is an accepted ritual.

Dieter

Dieter Menne wrote:
> Christopher W. Ryan <cryan <at> binghamton.edu> writes:
> 
>> Is there a way to automate fitting and assessing loglinear models for
>> several nominal variables . . . something akin to step or drop1 or add1
>> for linear or logistic regression?
> 
> Not strictly for loglinear, but glm works with stepAIC. Make sure that 
> in the field you are working this approach is an accepted ritual.
> 
> Dieter
> 
Dieter was kind.  I would say the following: Make sure your colleagues 
are interested in non-reproducible results, overfitting, incorrect 
P-values, and incorrect confidence limits before proceeding.

Frank


-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University

Dieter Menne wrote:
> 
> Christopher W. Ryan <cryan <at> binghamton.edu> writes:
> 
>> 
>> Is there a way to automate fitting and assessing loglinear models for
>> several nominal variables . . . something akin to step or drop1 or add1
>> for linear or logistic regression?
> 
> Not strictly for loglinear, but glm works with stepAIC. Make sure that 
> in the field you are working this approach is an accepted ritual.
> 
> Dieter
> 
> 
There is also the package formerly known as "dRedging":
http://r-forge.r-project.org/projects/mumin/


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Hi,

you could also take a look at:
http://www.nabble.com/finding-best-fitting-model-td22852224.html


Bart


ryancw wrote:
> 
> Is there a way to automate fitting and assessing loglinear models for
> several nominal variables . . . something akin to step or drop1 or add1
> for linear or logistic regression?
> 
> Thanks.
> 
> --Chris
> -- 
> Christopher W. Ryan, MD
> SUNY Upstate Medical University Clinical Campus at Binghamton
> 40 Arch Street, Johnson City, NY  13790
> cryanatbinghamtondotedu
> 
> "If you want to build a ship, don't drum up the men to gather
wood,
> divide the work and give orders. Instead, teach them to yearn for the
> vast and endless sea."  [Antoine de St. Exupery]
> 
> ______________________________________________
> R-help at r-project.org 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.
> 
> 
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