Talk:Pre- and post-test probability: Difference between revisions

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Created page with '==Motivation for having own article== I forked this section from Likelihood ratios in diagnostic testing, partly to provide a common fork som that one and [[pos...'
 
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==Motivation for having own article==
I forked this section from [[Likelihood ratios in diagnostic testing]], partly to provide a common fork som that one and [[positive predictive value]], and partly because so many incoming links (such as positive pre-test probability, negative post-test probability, negative post-test odds etc) cannot feasibly be redirected to a section. [[User:Mikael Häggström|Mikael Häggström]] ([[User talk:Mikael Häggström|talk]]) 08:30, 30 January 2011 (UTC)
 
== Confusion about example ==
 
I'm confused about why go through all the rigamarole with odds and likelihood ratios, etc in the given example.
 
What I take it we're after is the post-test probability. I.e., what we want to know is
<math> P( Cancer = True | Test = True) </math>.
 
But that can be read directly off of the chart given in the article, in one calculation, by the definition of conditional probability:
:<math> P( Cancer = True | Test = True) = \frac{ P(Cancer = True \and Test = True)}{P(Test=True)} = \frac{2}{2+8} = 0.10</math>
 
That seems '''way''' easier than the complicated 4 step process described in the example. So why would you ever do it that way?