Plot versus criterion values

Command

Statistics ROC curves Plot versus criterion values

Description

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.

Required input

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").

Options:

• Show 95% Confidence Intervals as:
  • error bars: show the 95% Confidence Interval of sensitivity and specificity as error bars
  • connected lines: show the 95% Confidence Interval of sensitivity and specificity as connected lines (recommended when number of criterion values is high)
  • do not show CI: do not show the 95% Confidence Interval of sensitivity and specificity in the graph.
• If the data require a logarithmic transformation (e.g. when the data are positively skewed), select the Logarithmic transformation option.

Graph

See also

• ROC curves: Introduction
• Interactive dot diagram
• Predictive values
• Interval likelihood ratios
• Comparison of ROC curves
• Format graph
• Graph legend
• Add graphical objects
• Reference lines