This seems to be more a statistics than an R problem.
Let's assume, one stratum is male and the other is female, and that you are giving estrogen. With women, it may be better to have more estrogen, with men to have less. Thus, if you recode
women: (more estrogen/less estrogen) -> (more appropriate/less appropriate)
men: (more estrogen/less estrogen) -> (less appropriate/more appropriate)
and if this reflects your hypothesis, it will solve your problem.
Knut
At 14:42 2003-12-11 +0100, you wrote:
Hello,
I've tried to analyze some data with a CMH test. My 3 dimensional contingency tables are 2x2xN where N is usually between 10 and 100.
The problem is that there may be 2 strata with opposite counts (the 2x2 contigency table for these are reversed), producing opposite odds ratios that cancle out in the overall statistics. These opposite counts are very important for my analysis, since they account for a dramatic difference.
Could you recommend alternative tests that take account for opposite counts? Would you suggest a different strategy to analyze such data?
thanks a lot for your suggestions,
Arne
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Knut M. Wittkowski, PhD,DSc ------------------------------------------ The Rockefeller University, GCRC Experimental Design and Biostatistics 1230 York Ave #121B, Box 322, NY,NY 10021 +1(212)327-7175, +1(212)327-8450 (Fax) [EMAIL PROTECTED] http://www.rucares.org/clinicalresearch/dept/biometry/
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