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:
- Using mean and standard deviation from ordinal variables to determine effect size (how big of a deal is this?)
- Transforming Cramer’s V to Cohen’s d (is there a better method?)
- 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.