Issues with effect size in CME

This past Thursday, I gave a short presentation on effect size at the SACME Spring Meeting in Cincinnati (a surprisingly cool city, by the way – make sure to stop by Abigail Street).  Instead of a talk about why effect size is important in CME, I focused on its limitations.  My expectation was feedback about how to refine current methods.  My main concerns:

  1. Using mean and standard deviation from ordinal variables to determine effect size (how big of a deal is this?)
  2. Transforming Cramer’s V to Cohen’s d (is there a better method?)
  3. How many outcome questions should be aggregated for a given CME activity to determine an overall effect? (my current minimum is four)

The SACME slide deck is here.  I got some good feedback at the meeting, which may lead to some changes in the approach I’ve previously recommended. Until then, if you have any suggestions, let me know.

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Filed under CME, Cohen's d, Cramer's V, Effect size, Statistics

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