Frank E Harrell Jr <[EMAIL PROTECTED]> writes: > On Thu, 11 Dec 2003 14:42:07 +0100 > <[EMAIL PROTECTED]> 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 > > > > I'm not sure about your specific problem, but in general you might think > of this as a binary or multinomial logistic model with strata x treatment > interactions, and get pooled treatment main effect + interaction effects, > which are equivalent to testing whether treatment is associated with > response for ANY stratum (without cancellation when signs of effects are > reversed). With the Design package, for example, you can do this easily > when the response is binary or ordinal: > > library(Design) > f <- lrm(y ~ treat*strat) > anova(f) # prints multiple d.f. test for treat as either main effect or > effect modifier > > Of course when you allow for a more general model such as this, the power > is diluted into multiple degrees of freedom when the effects really do not > vary very much over strata.
Also note the woolf() function given in the examples section of the help for mantelhaen.test. -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
