similar to: using "cochran.test()" as a "mcnemar.test()" ?

Hi! I would like to conduct a Cochran`s Q Test in R, but have not found any suitable function. My first idea was: J <- as.table(matrix(c(6,16,2,4),ncol=2, dimnames = list("C" = c("Favorable","Unfavorable"),"Drug A Favorable"=c("B Favorable","B Unfavorable")))) L <- as.table(matrix(c(2,4,6,6),ncol=2, dimnames =

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

Dear all, I am trying to look for a built in function that performs the cochran Q test. that is, cochranq.test(X) where X is a contingency table (maybe a matrix or data.frame). The output will naturally be the test statisitcs, p-value, etc. A quick search on Google gives me the cochran.test in the 'outlier' package, but I had a look at the description of the test and it doesn't look

Does anyone know which package include the computation of Cochran’s Q statistic in R? jlfmssm [[alternative HTML version deleted]]

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]]

Hi, I have been trying to use the function cochran.test from the Outliers package to test for homogeneity of variance. This works well except when I use transformed data. Would anyone have an idea why it doesn't work and how I could do the cochran test on transformed data? Thanks, Stephanie >library(outliers) > set.seed(1234) > x=rnorm(100) >

Hello, I'm new in this R world and I don't know much about statistics, but now I have to analize some data and I've got some first queries yet: I have 5 sets of area mesures and each set has 5 repetitions. My first step is to check data looking for outliers. I've used the outliers package. I have to use the cochran test and the grubbs test in case I find any outlier. The problem

Hello, I am hoping someone can clarify why I might obtain a quite different value in R & SPSS for a McNemar test I ran. Firstly, here is the R syntax & output R OUTPUT > mctest <- as.table(matrix(c(128,29,331,430), + ncol =2, dimnames = list(group=c("preMHT","postMHT"), + assault=c("yes","no")))) > mctest assault

Does anyone know of another version of the Mcnemar test that provides: 1. Odds Ratios 2. 95% Confidence intervals of the Odds Ratios 3. Sample probability 4. 95% Confidence intervals of the sample probability Obviously the Odds Ratios and Sample probabilities are easy to calculate from the contingency table, but I would appreciate any help on how to calculate the confidence

Hello sir: How can I perform McNemar (paired chi square test) by using R? Thanks! ------------------------------ ******************************************* Xin Meng Capitalbio Corporation National Engineering Research Center for Beijing Biochip Technology BioPharma-informatics & Software Dept. Research Engineer Tel: +86-10-80715888/80726868-6438 Fax: +86-10-80726790 Email??xmeng

Hello, I have some satellite tag time-at-depth (TAD) frequency data that I would like some help with. The data was transmitted via satellite as percent time spent in each of 7 depth bins (0m, 0-1m, 1-10m, 10-50m etc.), binned over 6-hour intervals. I categorized each row of data corresponding to a date and time into summer vs. winter, and day vs. night, and then summed and averaged the given

I am working with the mcnemar.test function and the help does not show a maintainer/author, but it is part of the stats package. My issue is that I want to use the test on 2 variables with possible values of 0:3, in one of the tests one of the variables does not have any 3's, so to make sure that the matrix is square I do: > x <- factor(x, levels=0:3) > y <- factor(y, levels=0:3)

Sir, I have a problem here while applying chisquare test to the following Data ( below the subject of this mail) ...when I wanted to test the significance using three different free statistical packages, here R, EpiInfo and OpenEpi. *Only OpenEpi accepts the test based on Cochran's Recommendations. * R says " chi squared approximation may be incorrect." Does it mean the same as

Dear List, I am looking for what B.S.Everitt refers to as Cochrane Method for testing independence in combined 2x2 contingency tables. Is it the same method as the Cochran-Mantel-Haenszel Chi-Squared Test for Count Data in R? Thanks, Serguei [[alternative HTML version deleted]]

Hi friends, I get different values for McNemar's test in R and SPSS. Which one should i rely on when the p values differ. I came across this problem when i started learning R and seriously give up on SPSS or any other proprietary software. Thank u in advance Output in SPSS follows *Crosstab* hsc Total ABN NE ABN tvs ABN Count 40 3 43 Row % 93.0% 7.0%

Dear sir, I am Shibu John from Thrombosis Research Institute India. It is a multidisciplinary organisation concerned with the interrelated problems of thrombosis and atherosclerosis. I was searching for Cochran armitage trend test program in R. Then I had seen your R coding for C-A trend test. I tried that in the R software. But I can?t run the program due the [Error: could not find function

Hi! I am searching for the Cochran-Armitage-trend-test. Is it included in an R-package? Thank you! --

In SAS, for a two-way (or 3-way, stratified) table, the CMH option in SAS PROC FREQ gives 3 tests that take ordinality of the factors into account, for both variables, just the column variable or neither. Is there an equivalent in R? The mantelhaen.test in stats gives something quite different (a test of conditional independence for *nominal* factors in a 3-way table). e.g. I'd like to

Hello dear R help group. My question is statistical and not R specific, yet I hope some of you might be willing to help. *Experiment settings*: We have a list of subjects. each of them went through two tests with the answer to each can be either 0 or 1. *Goal*: We want to know if the two experiments yielded different results in the subjects answers. *Statistical test (and why it won't

I want to understand ANOVA better. But a few textbook that I have do not describe Cochran's Theorem in details. Could somebody recommend a book for me?