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The role of statistical power

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Title_Discussion_Topic The role of statistical power
Name_Topic_Initiator Peter Bacchetti
Online_Journal_Club_Meeting Meeting 3
Description - Problem to be explored In this article, Gigerenzer appears to me to provide an example of an odd phenomenon: many people seem to be big fans of power calculations despite explicitly rejecting the automatic decision making and dichotomization of a study’s results that the usual “hypothesis testing” framework requires. When Gigerenzer writes (page 602), “there were finally 9 researchers who computed the power of their tests,” it sounds almost like he is endorsing post-hoc power calculations. Power is irrelevant for interpreting completed studies, whether calculated before the study or (more accurately) after. In addition, the definition of power requires dichotomizing the results of a study as P<alpha or not. This is a severe mismatch with how many of these same people advocate that a study’s results should be reported and interpreted (see, e.g., here ). I’ve argued that reporting power calculations only serves to promote poor interpretation of studies’ results, along the very lines that Gigerenzer (and others) criticize.
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Topic revision: r2 - 02 Dec 2013 - 11:06:15 - MaryBanach
 

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