Dear Forum members,
I have a dataset containing about 1000 observations with a binary reference variable (gold_standard = cult_positive =1/0) and two continouus predictor variables of a test between 0 and 1000 (UF_lc UF_bact). I want to define cut-off variables c1 and c2 for the test, that maximise the youden-index.
If I run the following commands
I got a very nice ROC curve and Area under ROC curve = 0.9217.
My questions are:
i) How is Stata drawing this curve? If there is only one prediction parameter (T) in the logit model, it is clear to me, that the ROC curve plots parametrically the false positive and true positive rate with T as the varying parameter. For two prediction parameters I don't understand the interpretation. Is it possible to label the different "cut-off values" for UF_lc and UF_bact for some points at the curve?
ii) Is there an easy way to get the combination c1, c2 of paramters so that a positive test defined as "UF_lc <= c1 and UF_bact <= c2" has the maximum youden index (sens+spec-1)?
Tanks in advance for your thoughts on this.
Best wishes
Martin
I have a dataset containing about 1000 observations with a binary reference variable (gold_standard = cult_positive =1/0) and two continouus predictor variables of a test between 0 and 1000 (UF_lc UF_bact). I want to define cut-off variables c1 and c2 for the test, that maximise the youden-index.
If I run the following commands
Code:
logistic cult_pos UF_lc UF_bact lroc
My questions are:
i) How is Stata drawing this curve? If there is only one prediction parameter (T) in the logit model, it is clear to me, that the ROC curve plots parametrically the false positive and true positive rate with T as the varying parameter. For two prediction parameters I don't understand the interpretation. Is it possible to label the different "cut-off values" for UF_lc and UF_bact for some points at the curve?
ii) Is there an easy way to get the combination c1, c2 of paramters so that a positive test defined as "UF_lc <= c1 and UF_bact <= c2" has the maximum youden index (sens+spec-1)?
Tanks in advance for your thoughts on this.
Best wishes
Martin
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