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?
Dieter was nominating this for the "fortunes" package in R. (Thanks Dieter)
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?
Or use a data reduction method (principal components, variable
clustering, etc.) or redundancy analysis (to remove individual
predictors before examining associations with Y), or fit the full model
using penalized maximum likelihood estimation. lasso and lasso-like
methods are also worth pursuing.
Cheers
Frank
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Ted Harding
Sent: Saturday, September 27, 2008 4:30 PM
To: [EMAIL PROTECTED]
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) <[EMAIL PROTECTED]>
Fax-to-email: +44 (0)870 094 0861
Date: 27-Sep-08 Time: 23:30:19
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