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Old Friday, November 01, 2013
Sarrial Banda's Avatar
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Default Sensitivity & Specificity


Respected members, I was studying psychology & came across these two terms i.e "Sensitivity & Specificity". I am stuck on these two & am unable to understand the relationship of Sensitvity with "True Positive prediction" & relationship of Specificity with "True Negative Prediction". The more I study, the more I get confused. Here is a googled explanation copied below for reference. Please help!!!!

Sensitivity and specificity are terms used to evaluate a clinical test. They are independent of the population of interest subjected to the test.

Positive and negative predictive values are useful when considering the value of a test to a clinician. They are dependent on the prevalence of the disease in the population of interest.

The sensitivity and specificity of a quantitative test are dependent on the cut-off value above or below which the test is positive. In general, the higher the sensitivity, the lower the specificity, and vice versa.

Source: http://ceaccp.oxfordjournals.org/content/8/6/221.full
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Old Saturday, November 16, 2013
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I was reading an article and I came across this.. See if it's helpful for you.

Sensitivity and specificity. According to the AMA Manual of Style, the term sensitivity is defined as "the proportion of individuals with the disease or condition as measured by the criterion standard who have a positive test result. " (The term criterion standard is preferred to the term gold standard and refers to the diagnostic standard for a disease or condition that is used as a basis of comparison for other tests. In other words, the criterion standard is the best test for a disease or condition. Although the AMA Manual of Style defines the terms specificity and sensitivity in terms of the criterion standard, the terms can be applied to any test.) For example, if a test were to have a sensitivity of 99%, then of 100 people who had the disease, 99 people would test positive.

The AMA Manual of Style defines specificity as "the proportion of those without the disease or condition as measured by the criterion standard who have negative results by the test being studied." For example, if a test were to have a specificity of 99%, then of 100 people who did not have the disease, 99 people would test negative.

Ideally, a good screening test will have a high sensitivity, and a good confirmatory test will have a high specificity. This distinction makes sense, because if you were to screen a large population, you would want to catch as many people with the disease as possible (high sensitivity), and when you were to confirm whether these people have a disease, you would want to weed out as many people as possible (high specificity). Ideally, the criterion standard (gold standard) would have both a high sensitivity and specificity and serve as the best single test for a disease or condition.

Or you can read this article.

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