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Statistical Reference Guide
Diagnostic performance
Testing the difference between the areas under two curves
Test if the area under curves is equal, equivalent, or not inferior to another.
You must have already completed the task:
Comparing two or more ROC curves
Activate the analysis report worksheet.
On the
Analyse-it
ribbon tab,
in the
Diagnostic Accuracy
group, click
Test
, and then click:
Option
Description
Equality
Test if the AUCs are equal.
Equivalence
Test if the AUCs are equivalent within a practical difference.
Non-inferiority
Test if the AUC is not inferior to another AUC.
The analysis task pane
Comparisons
panel opens.
In the analysis task pane, under the hypotheses drop-down list:
If testing a hypothesis of equivalence, in the
Contrast
drop-down list, select the comparisons, and then in the
Equivalent difference
, type the smallest practical difference that would be considered the same.
If testing a hypothesis of non-inferiority, in the
Standard
drop-down list, select the standard diagnostic test, and then in the
Smallest difference
edit box, type the smallest difference that would be considered inferior.
Optional:
To compare the p-value against a predefined significance level, in the
Significance level
edit box, type the maximum probability of rejecting the null hypothesis when in fact it is true (typically 5% or 1%).
Click
Recalculate
.
Related concepts
Difference between the areas under two curves
Available in Analyse-it Editions
Method Validation edition
Ultimate edition
What is Analyse-it?
What's new?
Administrator's Guide
User's Guide
Statistical Reference Guide
Distribution
Compare groups
Compare pairs
Contingency tables
Correlation and association
Principal component analysis (PCA)
Factor analysis (FA)
Item reliability
Fit model
Method comparison / Agreement
Measurement systems analysis (MSA)
Reference interval
Diagnostic performance
Measures of diagnostic accuracy
Estimating sensitivity and specificity of a diagnostic test
Comparing the sensitivity and specificity two diagnostic tests
ROC plot
Plotting a single ROC curve
Comparing two or more ROC curves
Area under the curve (AUC)
Testing the area under the curve
Difference between the areas under two curves
Testing the difference between the areas under two curves
Decision thresholds
Decision plot
Finding the optimal decision threshold
Predicting the decision threshold
Study design
Survival/Reliability
Control charts
Process capability
Pareto analysis
Study Designs
Bibliography
Version 6.15
Published 18-Apr-2023
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