Specificity: Difference between revisions
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--------------------------------------------------------------------------------------------------------------> | -------------------------------------------------------------------------------------------------------------->Specificity is the probability of a negative result in healthy patients '''b/b+d'''. | ||
Specificity is the probability of a negative result in healthy patients '''b/b+d'''. | |||
The specificity of a test reflects on the ability of a test to identify true negatives. | The specificity of a test reflects on the ability of a test to identify true negatives. | ||
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For example, if he had a mammography screening for breast cancer with 100% specificity, it would mean that '''all''' women without breast cancer that underwent screening tested negative. | For example, if he had a mammography screening for breast cancer with 100% specificity, it would mean that '''all''' women without breast cancer that underwent screening tested negative. | ||
We have a group of 4 women - Lucy, Jane, Cathie and Lenka. | We have a group of 4 women - Lucy, Jane, Cathie and Lenka. has breast cancer. Lucy has breast cancer. All women undergo the screening mammography. It detects Lucy and Jane as positive. Lucy is really positive. Jane is a false positive. Cathie and Lenka are actually negative. Nobody is falsely negative. When you enter the values into the formula above, we find that the test showed about 67% specificity (specificity = 0.67). One woman with no tumor was identified as positive (we have one woman falsely positive). | ||
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Latest revision as of 18:21, 8 December 2014
Specificity is the probability of a negative result in healthy patients b/b+d. The specificity of a test reflects on the ability of a test to identify true negatives.
For example, if he had a mammography screening for breast cancer with 100% specificity, it would mean that all women without breast cancer that underwent screening tested negative. We have a group of 4 women - Lucy, Jane, Cathie and Lenka. has breast cancer. Lucy has breast cancer. All women undergo the screening mammography. It detects Lucy and Jane as positive. Lucy is really positive. Jane is a false positive. Cathie and Lenka are actually negative. Nobody is falsely negative. When you enter the values into the formula above, we find that the test showed about 67% specificity (specificity = 0.67). One woman with no tumor was identified as positive (we have one woman falsely positive).
Test | Disease + | Healthy- | Total |
+ | a | b | a+b |
- | c | d | c+d |
Total | a+c | b+d | n |

Links[edit | edit source]
Related Article[edit | edit source]
Bibliography[edit | edit source]
- BENCKO, Vladimír. Epidemiologie, výukové texty pro studenty. 2nd edition. Karolinum, 2002. ISBN 80-246-0383-7..
- BENCKO, Vladimír. Biomedicínská statistika. 1st edition. Karolinum, 2003. ISBN 80-246-0763-8.
- KUPKA, Karel. Nukleární medicína. 1st edition. Karolinum, 2007. ISBN 978-80-903584-9-2.