From wikipedia (just to say that you can get information from many
sources):
Sensitivity is the proportion of people that tested positive of all the
positive people tested; that is (true positives) / (true positives +
false negatives). It can be seen as the probability that the test is
positive given that the patient is sick. The higher the sensitivity, the
fewer real cases of diseases go undetected (or, in the case of the
factory quality control, the fewer faulty products go to the market).
Specificity is the proportion of people that tested negative of all the
negative people tested; that is (true negatives) / (true negatives +
false positives). As with sensitivity, it can be looked at as the
probability that the test is negative given that the patient is not
sick. The higher the specificity, the fewer healthy people are labeled
as sick (or, in the factory case, the less money the factory loses by
discarding good products instead of selling them).
Melissa
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of
James Whanger
Sent: Sunday, September 09, 2007 10:16 AM
To:
[hidden email]
Subject: Re: [SPSSX-L] Sensitivity analyses
Are you referring to the sensitivity and specificity of correctly
identifying cases possessing and not possessing, respectively, a
particular characteristic? These terms are generally used in medical
screening and diagnosis, but the idea may be extended to other types of
decision making.
Jim
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