similar to: Cochran-Mantel-Haenszel problem

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

Hi all, Does anyone know if an R function for the Mantel-Haenszel chi-square for a 2x2 table exists? I’ve also seen it called the randomization Q statistic. Note that I’m not looking for the Cochran-Mantel-Haenszel…I did see that out there as cmh.test. Thanks in advance, Jeff Internal Virus Database is out-of-date. Checked by AVG Free Edition. 11:27 AM [[alternative HTML version

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]]

Dear R users, I am happy to announce the new package `samplesizeCMH` is now available on CRAN <https://cran.r-project.org/package=samplesizeCMH>. The `samplesizeCMH` package will compute power and sample size for the Cochran-Mantel-Haenszel test for stratified 2x2 tables. There are also several helper functions for working with 2x2 tables, such as converting a proportion into an odds

Dear R users, I am happy to announce the new package `samplesizeCMH` is now available on CRAN <https://cran.r-project.org/package=samplesizeCMH>. The `samplesizeCMH` package will compute power and sample size for the Cochran-Mantel-Haenszel test for stratified 2x2 tables. There are also several helper functions for working with 2x2 tables, such as converting a proportion into an odds

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

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 of an R function for computing the Greenland-Robins variance for Mantel-Haenszel relative risks? Thanks Frank -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University

Hello, I am searching for an R-Package that does an exentsion of the Mantel-Haenszel test for ordinal data as described in Liu and Agresti (1996) "A Mantel-Haenszel type inference for cummulative odds ratios". in Biometrics. I see packages such as Epi that perform it for binary data and derives a varaince for it using the Robbins and Breslow variance method. As well as another pacakge

Dear R users, In metafor 1.6-0, the Mantel-Haenszel method is implemented by the rma.mh() function. I have observed that the sum of the weights computed by weights(x) doesn't add to 100% when x is an object of class rma.mh. The consequences of this fact can be clearly seen when a forest diagram is drawn with forest(x), which calls weights(x) (or more precisely, the method weights.rma.mh()

Dear list I would like to compute a Mantel-Haenszel chi-square in which the matching variable is a continuous variable. The MH chi-square is used to assess the relationship between two categorical variables at each level or strata defined by a third variable. Specifically I would like to know if there is a straightforward way to divide the matching variable into levels, in which each level has a

Has anyone written R code for extended Mantel-Haenszel Tests- as described in Section 8.4.5 (eq. 8.18) of Agresti's book "Categorical Data Analysis"? In other words, I would like to use column scores to test for a location shift for different groups as defined by the row variable in a set of rxs tables. In addition, I would like to use row and column scores to test for a linear

Dear R'ers, When I used S-plus i wrote a small program for a Mantel-Haenszel test for trend (I think it worked). Unfortunately I can't get it working in R. It appears as if my use of 'el' is the problem but I can't sort it out. Error in apply(array, c(, 2, 3), function(el) el * 1:s) : argument is missing, with no default Further down in the program I use 'el'

Hi there, is there any way to compare 2 odds ratios? I have two tests that are supposed to detect a disease presence. So for each test, I can compute an odds ratio. My problem is how can I compare the 2 tests by testing whether the 2 odds ratios are the same? Appreciate

Just a general question concerning the woolf test (package vcd), when we have stratified data (2x2 tables) and when the p.value of the woolf-test is below 0.05 then we assume that there is a heterogeneity and a common odds ratio cannot be computed? Does this mean that we have to try to add more stratification variables (stratify more) to make the woolf-test p.value insignificant? Also in the

I have a print method for a set of statistical tests, vcdExtra::CMHtest, for which I'd like to have more sensible printing of pvalues, as in print.anova(). [Testing this requires the latest version of vcdExtra, from R-Forge **|install.packages("vcdExtra", repos="http://R-Forge.R-project.org")|** ] With my current print method, I get results like this, but all Prob values

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

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 =

I've read the Wiki on using asterisk's built-in transfer options (#8 and #6). They work fine but how does one cancle an attended transfer? Example: I have person on phone, I hit #6 to being att-transfer. I enter Sally's extension. I let it ring for a few seconds. Sally never picks up but her voicemail does. How do I hangup her voicemail and resume the previous call? The example on the

Often, when exploring a dataset, I'd like to plot several very different Y variables against the same X variable, in panels stacked one over the other. Is there an easy way to do this? I'd like to achieve an elegant look similar to the look achieved by lattice in conditioned plots--for instance no space between panels. But unlike in straightforward conditioned plot, each panel may be on a