John Sorkin wrote:
Of course Prof Baer is correct the positive predictive value (PPV)
and the negative predictive values (NPV) serve the function of
providing conditional post-test probabilities PPV: Post-test
probability of disease given a positive test NPV: Post-test
probability of no disease given a negative test.
Further, PPV is a function of sensitivity (for a given specificity in
a population with a given disease prevalence), the higher the
sensitivity almost always the greater the PPV (it can by unchanged,
but I don't believe it can be lower) and as NPV is a function of
specificity (for a given sensitivity in a population with a given
disease prevelance), the higher the specificity almost always the
greater the NPV (it can by unchanged, but I don't believe it can be
lower) .
The PPV and NPV can be anything between 0 and 1 regardless of
sensitivity and specificity. Just apply the test to populations with a
prevalence of 0 or 1. The former gives you a PPV of 0 and an NPV of 1
since none of the positive and none of the negative will be true
positive. And vice versa.
--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907
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