This is a question concerning the bootstrap function of the HMISC-library
written by Harrell (I use SPLUS 3.3 under windows95). I am interested in
the corrected R-square of a final fitted model (logistic regression using
the lrm()-function) to have an estimate 'how stabile' the model is, i.e.
how much the uncorrected R-squared may be too optimistic, assuming that
this model is used for other samples.
1) is the corrected R-square ('index.corrected') the mean of the
R-squares over the bootstrap replications or is it sort of a lower bound
of the `true` R-square (like a confidence interval)? Is there a confidence
interval for the index.corrected too?
2) Could I get an answer to the same question by doing cross validation
and what would be the major (dis-)advantage?
I know I have to read the Efron and Tibshirani book on it - probably
someone knows where to start best here.
Thanks for any comments!
yours Matthias
----------------------------------------
Matthias Richard (doctoral candidate)
Center for Research on Psychotherapy
Christian-Belser-Str. 79a
70593 Suttgart
Germany
email: richard@psyres-stuttgart.de
telephone: ++49-711-6781-408
http://www.psyres-stuttgart.de
COST Action B6:
'Efficient Psychotherapy of Eating Disorders'
(COoperation of Science and Technology in the European Union)
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