[visionlist] analyzing medians

[Todd S. Horowitz]

I have a puzzle about analyzing RT data. I prefer to use medians rather than means, because I am suspicious of all of the various data trimming procedures. However, medians seem to be creating some problems when I run ANOVAs on the data.

I'm working with some data. Let's say there are 4 factors, A, B, C, and D. However, the critical analyses collapse over the levels of factor D. My collaborator sent me an analysis where she took the ABCD medians, then collapsed by taking the means of those medians across factor D, then running the ANOVA. I decided that was incorrect, and directly computed the ABC medians from the raw data, then ran an ANOVA. The results were subtly different, pushing the 3-way interaction across the p = .05 line. However, it then ocurred to me that the ANOVA does just the same thing as what my collaborator did: the A main effect takes the means of the medians. If I were to directly compute the A medians from the raw data, and run a one-way ANOVA, I would probably get subtly different results from the ANOVA on the ABC medians.

So, what's the correct approach to this analysis? Do I give up and work with means? Always recompute the medians from the raw data for each effect separately? Or is it perfectly OK to just take the mean of medians?

thanks
Todd


Todd S. Horowitz, PhD
Assistant Professor of Ophthalmology
	Harvard Medical School
Associate Director
	Visual Attention Lab
	Brigham & Women's Hospital
64 Sidney Street, Suite 170 
Cambridge, MA 02139
phone:  (617) 768-8813
fax:    (617) 768-8816
http://search.bwh.harvard.edu/



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