Plot versus criterion values
In this graph (part of ROC curve analysis) the sensitivity and specificity, and optionally their 95% Confidence Intervals, are plotted against the different criterion values.
Variable: identify the variable of interest.
Classification variable: select or enter a dichotomous variable indicating diagnosis (0=negative, 1=positive). If diagnosis is coded differently than using the values 0 and 1, you can use the IF function to transform the codes into 0 and 1 values, e.g. IF(RESULT="pos",1,0).
Select: (optionally) a selection criterion in order to include only a selected subgroup of cases (e.g. AGE>21, SEX="Male").