[R] FW: logistic regression

Bert Gunter gunter.berton at gene.com
Mon Sep 29 02:25:57 CEST 2008


The Inferno awaits me -- but I cannot resist a comment (but DO look at
Frank's website).

There is a deep and disconcerting dissonance here. Scientists are
(naturally) interested in getting at mechanisms, and so want to know which
of the variables "count" and which do not. But statistical analysis --
**any** statistical analysis -- cannot tell you that. All statistical
analysis can do is build models that give good predictions (and only over
the range of the data). The models you get depend **both** on the way Nature
works **and** the peculiarities of your data (which is what Frank referred
to in his comment on data reduction). In fact, it is highly likely that with
your data there are many alternative prediction equations built from
different collections of covariates that perform essentially equally well.
Sometimes it is otherwise, typically when prospective, carefully designed
studies are performed -- there is a reason that the FDA insists on clinical
trials, after all (and reasons why such studies are difficult and expensive
to do!).

The belief that "data mining" (as it is known in the polite circles that
Frank obviously eschews) is an effective (and even automated!) tool for
discovering how Nature works is a misconception, but one that for many
reasons is enthusiastically promoted.  If you are looking only to predict,
it may do; but you are deceived if you hope for Truth. Can you get hints? --
well maybe, maybe not. Chaos beckons.

I think many -- maybe even most -- statisticians rue the day that stepwise
regression was invented and certainly that it has been marketed as a tool
for winnowing out the "important" few variables from the blizzard of
"irrelevant" background noise. Pogo was right: " We have seen the enemy --
and it is us."

(As I said, the Inferno awaits...)

Cheers to all,
Bert Gunter

DEFINITELY MY OWN OPINIONS HERE!



-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of David Winsemius
Sent: Saturday, September 27, 2008 5:34 PM
To: Darin Brooks
Cc: r-help at stat.math.ethz.ch; ted.harding at manchester.ac.uk
Subject: Re: [R] FW: logistic regression

It's more a statement that it expresses a statistical perspective very  
succinctly, somewhat like a Zen koan.  Frank's book,"Regression  
Modeling Strategies", has entire chapters on reasoned approaches to  
your question.  His website also has quite a bit of material free for  
the taking.

-- 
David Winsemius
Heritage Laboratories

On Sep 27, 2008, at 7:24 PM, Darin Brooks wrote:

> Glad you were amused.
>
> I assume that "booking this as a fortune" means that this was an  
> idiotic way
> to model the data?
>
> MARS?  Boosted Regression Trees?  Any of these a better choice to  
> extract
> significant predictors (from a list of about 44) for a measured  
> dependent
> variable?
>
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org 
> ] On
> Behalf Of Ted Harding
> Sent: Saturday, September 27, 2008 4:30 PM
> To: r-help at stat.math.ethz.ch
> Subject: Re: [R] FW: logistic regression
>
>
>
> On 27-Sep-08 21:45:23, Dieter Menne wrote:
>> Frank E Harrell Jr <f.harrell <at> vanderbilt.edu> writes:
>>
>>> Estimates from this model (and especially standard errors and
>>> P-values)
>>> will be invalid because they do not take into account the stepwise
>>> procedure above that was used to torture the data until they
>>> confessed.
>>>
>>> Frank
>>
>> Please book this as a fortune.
>>
>> Dieter
>
> Seconded!
> Ted.
>
> --------------------------------------------------------------------
> E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk>
> Fax-to-email: +44 (0)870 094 0861
> Date: 27-Sep-08                                       Time: 23:30:19
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