"Frequent lab testing isn't very useful"
@03:37: "We've all been told that data are important, and that more is the future."Below, two antecedent clips referred to in the foregoing:
From my grad thesis:
No diagnostic test or screening device is perfect. Errors of omission and commission occur...the definition of an accuracy rate can be done in a few different ways, and these are often confused in casual or uninformed communication...It is an important fact that predictive values do depend on overall prevalence rates...As the prevalence of a condition becomes rare, PPV [“Positive Predictive Value”] drops too, sometimes surprisingly so. For example, a test with sensitivity and specificity each equal to 99% is generally considered quite precise, relative to most diagnostic procedures. Yet for a condition with a not-so-rare prevalence of one per hundred, the odds on being affected [a “true positive”] given a positive test outcome are (.99/.01 x .01/.99) = 1 , i.e., among all positive results only 50% are truly affected! For a prevalence rate of one per thousand, the PPV is only about .10. These low numbers raise serious ethical and legal questions concerning action to be taken following positive test outcomes. - Finkelstein & Levin, Statistics for Lawyers.Color me firmly Bayesian (as well as a Chebychev-ist).
More to come...