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Re: st: PSEUDO R2
At 09:28 AM 12/5/2003, you wrote:
That is not ideal.
I am estimating grouped data logistic models using glogit or simply
using regress with analytical weights
generate double lcrp=log(ntprop/(pop-ntprop))
generate double wt1=ntprop*(pop-ntprop)/pop
glogit ntprop pop clprop $xvars $zvars $tvars
regress lcrp clprop $xvars $zvars $tvars [w=wt1]
If I want to get a measure of goodness of fit I might use the squared
correlation between y and yhat
regress lcrp clprop $xvars $zvars $tvars
corr yhat1 lcrp
Is that correct?
See the book by Hosmer & Lemeshow (Applied Logistic Regression) for an
excellent and extensive basic discussion on assessing fit.
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Constantine Daskalakis, ScD
Biostatistics Section, Thomas Jefferson University,
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