[R] predict.lrm ( Design package) poor performance?

[Chris Mcowen]

Thats great thanks

I guess it is hard to not use % as a performance measure when that is what is commonly used in everyday life.

So when i come to predicting the response of new data ( using the estimated mean Y ) which i am more comfortable with i can say -

Species A - 2.12 - Therefore this is category 2
Species B - 2.72 - Therefore this is category 3

(on a side note, i had no species with a rating of 6 - the upper category?)

The problem comes in explaining this to my peers who are non-statsistcally minded. What you are saying is if i bootstrapp and report the c-values and Bieber scores etc this is sufficient to give an indication of confidence?



On 22 Sep 2010, at 12:36, Frank Harrell wrote:


% correct is an improper scoring rule and a discontinuous one to boot.  So it
will not always agree with more proper scoring rules.

When you have a more difficult task, e.g., discriminating more categories,
indexes such as the generalized c-index that utilize all the categories will
recognize the difficulty of the task and give a lower value.  No cause for
alarm.

Frank

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