On Wed, Jan 20, 2010 at 12:39 AM, Susan Bosco <susanbosco86@yahoo.com>wrote:

> Dear Sean,
>
> Thank you so much for  the help.
>
> I tried with a range of thresholds from 0-0.9..As you had mentioned,the
> true positive rates no doubt increased with thresholds below 0.9.However I
> did get some false positive rates even at a minimum threshold of 0.1.Could
> you kindly explain the reason?
>
> Is there any method of finding the optimal threshold,maximizing the true
> positive rates while minimizing the false positives,instead of randomly
> choosing between 0-0.9?
>
>
Hi, Susan.  The ROC curve IS that method.  The ROC curve represents ALL
thresholds as applied to the data.  If you plot with show.thresh=TRUE, you
will see the thresholds that were tried and where they are on the curve.

If the threshold to which you are referring is the one that you used to
determine the variable you called "state", then we are talking about two
different things.  The "truth" variable is meant to be assigned by some
source other than the data themselves.  If you do not know the true state of
your samples and find yourself assigning the state the data, then ROC curve
analysis will not be of any use.

Sean


> Thanks in advance,
> Susan.
>
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