search for: mh_test

Estimados Para analizar tres muestras cualitativas independientes se utiliza Cochran-Mantel-Haenszel test ?Cual script es el adecuado para analizar tres variables dependientes? en MCNEMAR solo se permite analizar dos variables cualitaticvas dependientes saludos José [[alternative HTML version deleted]]

Hello all, I wish to perform a mcnemar test for a 3 by 3 matrix. By running the slandered R command I am getting a result but I am not sure I am getting the correct one. Here is an example code: (tt <- as.table(t(matrix(c(1,4,1 , 0,5,5, 3,1,5), ncol = 3)))) mcnemar.test(tt, correct=T) #And I get: McNemar's Chi-squared

Hello people, I am in need for testing Marginal Homogeneity for sparse (more then 2X2) matrixes. After searching, what I found by now is that for more then 2 by 2 matrixes, one turns to "stuart maxwell tests" that are available in two packages: irr - see: stuart.maxwell.mh coin - see: mh_test But I couldn't find in the documentation how valid the results are for sparse matrixes, and if the validity is indeed compromised (as I suspect it might be), I wasn't able to find an out-of-the-box alternative function to use. A search in google gave me a link to this article: http://www....

...0 3,2,1,0 3,2,2,0 3,2,3,0 3,2,4,0 3,3,1,0 3,3,2,1 3,3,3,0 3,3,4,71 I can run the following code, but am unsure if the Log-linear model is inappropriate given the large number of zero cells in my matrix. I've had a look for permutation based equivalents to avoid this issue, but can only find mh_test in the coin package, which I don't think is appropriate as none of my factors can be considered to blocking? # Import data COR<-read.table('Independence of traits.csv',header=T,sep=',',strip.white=T) # Transform data into an appropriate table form COR.tab<-xtabs(Count~S...

Dear all, I am having a hard time to figure out a suitable test for the match between two nominal classifications of the same set of data. I have used hierarchical clustering with multiple methods (ward, k-means,...) to classify my dat into a set number of classesa, and I would like to compare the resulting automated classification with the actual - objective benchmark one. So in principle I