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Re: st: Goodness of fit
From
Mikkel Brabrand <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: Goodness of fit
Date
Wed, 4 May 2011 13:23:17 +0200
Thanks for the reply.
The thing is, that I am validating the score and thus not performing a new logistic regression (and then unable to use the postestimation commands).
I have calculated a coefficient in the development cohort and am reusing this in the validation set. This is why I need to calculate goodness of fit by hand.
Mikkel
Den 03/05/2011 kl. 14.24 skrev Neil Shephard:
> On Tue, May 3, 2011 at 1:02 PM, mikkelbrabrand <[email protected]> wrote:
>> I have developed a risk scoring system that I'm trying to validate. It was
>> originally developed in one cohort, and I am now validating it in a new,
>> independent, cohort. However, I am unsure how to test for goodness-of-fit
>> using Hosmer-Lemeshow's test.
>>
>> First question: When validating my score, is it not correct that I should
>> use
>> the observed mortality (my endpoint) from the development cohort to estimate
>> the expected mortality in my validation cohort?
>>
>> Second question: When calculating the Chi-square between the observed and
>> expected mortality, should my formula not be: (observed-expected)^2/
>> (expected*1-expected/N (in this stratum))?
>>
>> Third question: How many degrees of freedome should I use? When I read the
>> book by Hosmer and Lemeshow (Applied logistic regression), in the section on
>> validation in an external cohort, I understand that the number of groups
>> equal the degrees of freedom, which in different from the ordinary method in
>> which the degrees of freedom is groups-2. Is this correct?
>
> You might want to check out -man logistic postestimation##estatgof-
> which implements the Hosmer-Lemeshow test (and permits you to specify
> the number of quantiles, and hence degrees of freedom).
>
> If you didn't know this existed you could have searched for it within
> Stata using -findit hosmer- and sifter through the results.
>
> Neil
>
>
> --
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