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libsvm Toolbox >> libsvm Toolbox > svmpartest

svmpartest

This function calculate the performance, based on Bayes theorem, of a

Calling Sequence

svmpartest(X)

Parameters

Outputs:

- Prevalence of disease:

- Test Sensibility with 95% confidence interval:

- Test Specificity with 95% confidence interval:

- False positive and negative proportions:

- Youden's Index:

- Test Accuracy:

- Mis-classification Rate:

- Positive predictivity with 95% confidence interval:

- Positive Likelihood Ratio:

- Negative predictivity with 95% confidence interval:

- Negative Likelihood Ratio:

- Error odds ratio:

- Diagnostic odds ratio:

- Discriminant Power:

- Test bias:

- Number needed to Diagnose (NDD):

Examples

X=[80 3; 5 20];

svmpartest(X)

Answer is:

Prevalence: 78.7%

Sensitivity (probability that test is positive on unhealthy subject): 94.1%
95% confidence interval: 89.1% - 99.1%
False negative proportion: 5.9%

Specificity (probability that test is negative on healthy subject): 87.0%
95% confidence interval: 73.2% - 100.0%
False positive proportion: 13.0%

Youden's Index (a perfect test would have a Youden index of +1): 0.8107

Accuracy or Potency: 92.6%
Mis-classification Rate: 7.4%

Predictivity of positive test (probability that a subject is unhealthy when test is positive): 96.4%
95% confidence interval: 92.4% - 100.0%
Positive Likelihood Ratio: 7.2
Moderate increase in possibility of disease presence

Predictivity of negative test (probability that a subject is healthy when test is negative): 80.0%
95% confidence interval: 64.3% - 95.7%
Negative Likelihood Ratio: 0.1
Large (often conclusive) increase in possibility of disease absence

Error odds ratio: 2.4000
Diagnostic odds ratio: 106.6667
Discriminant Power: 2.6
A test with a discriminant value of 1 is not effective in discriminating between affected and unaffected individuals.
A test with a discriminant value of 3 is effective in discriminating between affected and unaffected individuals.
Test bias: 0.9765
Test underestimates the phenomenon
Number needed to Diagnose (NDD): 1.2

Created by Giuseppe Cardillo
giuseppe.cardillo-edta@poste.it

To cite this file, this would be an appropriate format:
Cardillo G. (2006). Clinical test performance: the performance of a
clinical test based on the Bayes theorem.
http://www.mathworks.com/matlabcentral/fileexchange/12705
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