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Re: st: Comparing risk scores


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Comparing risk scores
Date   Tue, 18 Oct 2011 12:36:56 +0100

I would recast this as a -logit- or -logistic- problem in which your
outcome is dead or alive. Depending on how you think about your
scores, they define predictors to be treated as they come or
predictors to be treated as a set of indicator variables (or in some
cases both).

 I don't think you are restricted to using one score or the other as predictor.

Nick

On Tue, Oct 18, 2011 at 12:11 PM, K Jensen <k.x.jensen@gmail.com> wrote:
> Maybe this is more of a stats question than a Stata one, but there are
> such a lot of good brains here...
>
> We are constructing point scores to indicate severity of risk  Death
> is the outcome. What is the best way of measuring the usefulness of
> the score?  The aim is to show a good gradient of risk.  Say the
> results for two different scores were:
>
> Score  Dead  Alive    %dead    Totals
> 0        12    136      9.9%      145
> 1        18    126     15.4%      144
> 2        18     62     26.2%       81
> 3        10      9     57.1%       20
> 4         2      0    100  %        3
> -------------------------------------
> Total:   60    333                393
>
> Score  Dead  Alive    %dead    Totals
> 0         8    174      4.6%      182
> 1        21    143     12.8%      164
> 2        22     19     53.7%       41
> 3         5      1     83.3%        6
> -------------------------------------
> TOTAL:   60    333                393
>
> Which is the better score?  What is the best way to measure its
> predictive power?  I understand that ROC type analysis doesn't really
> apply here.  Some measure of R-squared?  AIC?
>
> Thankyou
>
> Karin
>
> PS) I have made up the data, so the numbers don't quite add up.  It is
> meant to be two different, competing scores on the same people.

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