Nov 08 2012 What makes a health professional science-based? We
advocate for evaluations of treatments, and treatment decisions,
based on the best research methods. We compile evidence based on
fair trials that minimize the risks of bias. And, importantly,
we consider this evidence in the context of the plausibility of
the treatment. The fact is, it’s actually not that hard to get a
positive result in a trial, especially when it’s sloppily done
or biased. And there are many ways to design a trial to
demonstrate positive results in some subgroup, as Kimball Atwood
pointed out earlier this week. And even when a trial is well
done, there remains the risk of error simply due to chance
alone. So to sort out true treatment effects, from fake effects,
two key steps are helpful in reviewing the evidence. 1. Take
prior probability into account when assessing data. While a
detailed explanation of Bayes Theorem could take several posts,
consider prior probability this way: Any test has flaws and
limitations. Tests give p