recommendation on B for validate.lrm () ?

Thanks so much for the reply it was exceptionally helpful!  A couple of
questions:

1. I was under the impression that k-fold with B=10 would train on 9/10,
validate on 1/10, and repeat 10 times for each different 1/10th.  Is this
how the procedure works in R?

2. Is the reason you recommend repeating k-fold 100 times because the
partitioning is random, ie not 1st 10th, 2nd 10, et cetera so you might
obtain slightly different results?





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Yes that's how it works, but a single run does not provide sufficient
precision unless your sample size is enormous.  When you partition into
tenths again the partitions will be different so yes there is some
randomness.  Averaging over 100 times averages out the randomness.  Or just
use the bootstrap with B=300 (depending on sample size).

Frank

Thanks so much for the reply it was exceptionally helpful!  A couple of
questions:

1. I was under the impression that k-fold with B=10 would train on 9/10,
validate on 1/10, and repeat 10 times for each different 1/10th.  Is this
how the procedure works in R?

2. Is the reason you recommend repeating k-fold 100 times because the
partitioning is random, ie not 1st 10th, 2nd 10, et cetera so you might
obtain slightly different results?

-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
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