Specificity of a test refers to its ability to detect -
High-Yield Explanation
When a screening test is used to diagnose a disease, the test outcome can be positive (diseased) or negative (healthy), while the actual health status of the person may be different.
In that setting
True positive → Diseased people correctly diagnosed as diseased.
False positive → Healthy people wrongly identified as diseased.
True negative → Healthy people correctly identified as healthy.
False negative → Diseased people wrongly identified as healthy.
There are two major statistical measures for the validity of a screening test : -
Sensitivity
Specificity
Sensitivity
It is the ability of a test to identify correctly all those who have the disease, i.e., true positive.
In other words sensitivity measures the percentage of sick people who are identified as having disease.
For example if a test is 90% sensitive, that means out of 100 diseased people, it will diagnose 90 (90% of diseased people will be diagnosed). Remaining 10% will be wrongly indentified as not having the disease, i.e., false negative.
Specificity
It is the ability of a test to identify correctly those who do not have the disease i.e., true negative
In other words specificity measures the percentage of well people who are identified as not having the disease.
For example, a 90 percent specificity means that 90% of nondiseased people will be identified as not having the disease. The remaining 10% will be wrongly classified as diseased, i.e., false positive.