Dear all,
Some functions like 'ROC(Epi)' can be used to perform ROC analyssi, but it
needs us to specify the fitting model in the argument. Now i have got the
predicted p-values (0,1) for the 0/1 response variable using some other
approach, see the following example dataset:
id mark predict.pvalue
1 1 0.927
2 0 0.928
3 1 0.928
..................
*mark* is the true classes, *predict.pvalue* is the predicted p-values,
which was used to determine the predicted classes. So i need to specify some
cut points for *predict.pvalue*, and then compare it with *mark*class,
generate the 2*2 tables, and then calculate some sensitivity,
specifity....statistcs, and ROC curve.
I have searched some functions, such as roc(analogue),'ROC(Epi),etc. They
may need to specify the fitting model in the codes or group varibles,
and may be not appropriate for my condition. I think that it should
have been performed in some package for ROC analysis.
Anybody can tell me which function is for this case?
Thanks very much.
--
With Kind Regards,
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Zhi Jie,Zhang ,PHD
Tel:+86-21-54237149
Dept. of Epidemiology,School of Public Health,Fudan University
Address:No. 138 Yi Xue Yuan Road,Shanghai,China
Postcode:200032
Email:[EMAIL PROTECTED]
Website: www.statABC.com
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