On Feb 9, 2012, at 4:45 PM, array chip wrote:
Hi, didn't hear any response yet. want to give it another try..
appreciate any suggestions.
My problem after reading this the first time was that I didn't agree
with the premise that logistic regression would provide a standard
error for a probability. It provides a standard error around an
estimated coefficient value. And then you provided no further details
or code to create a simulation, and there didn't seem much point in
trying to teach you statistical terminology that you were throwning
around in a manner that seems rather cavalier , .... admittedly this
being a very particular reaction from this non-expert audience of one.
John
________________________________
To: "r-help@r-project.org" <r-help@r-project.org>
Sent: Wednesday, February 8, 2012 12:11 PM
Subject: [R] standard error for lda()
Hi, I am wondering if it is possible to get an estimate of standard
error of the predicted posterior probability from LDA using lda()
from MASS? Logistic regression using glm() would generate a standard
error for predicted probability with se.fit=T argument in predict(),
so would it make sense to get standard error for posterior
probability from lda() and how?
Another question about standard error estimate from glm(): is it ok
to calculate 95% CI for the predicted probability using the standard
error based on normal apprximation, i.e. predicted_probability +/-
1.96 * standard_error?
Thanks
John
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______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
