similar to: metafor: weights computation in Mantel-Haenszel method

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

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 Thanks in advance, Jeff Internal Virus Database is out-of-date.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

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

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 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]]

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

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

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'

A new package is now available via CRAN, called metafor. The metafor package consists of a collection of functions for conducting meta-analyses in R. Fixed- and random-effects models (with and without moderators) can be fitted via the general linear (mixed-effects) model. For 2x2 table data, the Mantel-Haenszel and Peto's method are also implemented. The package also provides various plot

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 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'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

Hi (R 2.13.1, OSX 10.6.8) I am trying to use predict.rma with continuous and categorical variables. The argument newmods in predict.rma seems to handle coviariates, but appears to falter on factors. While I realise that the coefficients for factors provide the answers, the goal is to eventually use predict.rma with ANCOVA type model with an interaction. Here is a self contained example

Dear all, I'm currently applying a mixed model approach to meta analysis using the package metafor. I use the "model.matrix()" function to create dummy variables. The option btt gives me the combined test for the dummies. Problem is, I don't know which indices I have to use, and can't really figure it out from the help file and the examples. I use following code : X <-

Dear R-experts! In a meta-analysis (metafor) I would like to assess the effect of two categorical covariates (A & B) whereas they both have 4 levels. Is my understanding correct that this would require to dummy-code (0,1) each level of each covariate (A & B)? However I am interested in the main-effects and the interaction of these two covariates and the dummy-coding would only allow to

Dear R-experts! I am working on some meta-analysis using the metafor package. I would like to extract values of the confidence intervals of the effect sizes of the single studies from an rma object. Those values are printed out when plotting a forest plot using the forest function on the rma object, however I was not able to locate them. Many thanks for your help! Jokel [[alternative HTML

Hello metafor users, I'm using metafor to perform a single-effect summary estimate of the raw proportion of patients experiencing a post-operative complication, and I'm interested in seeing if this proportion differs between the three most commonly used surgical techniques. The software is working as expected, but I would like to double check on the interpretation of my mixed-effect model

Dear R community, I'm using the ,metafor'-package by Wolfgang Viechtbauer (Version: 0.5-5) to calculate random-effects meta-analyses using Correlations and Sample Sizes as the raw data. (By the way: Really a nice piece of work, Wolfgang! Thanks heaps.) I specified the "rma.uni' function so that it looks like this: MAergebnis<-rma.uni(ri=PosOutc, ni=N,

I'm puzzled by the behaviour of factors in rma models, see example and comments below. I'm sure there's a simple explanation but can't see it... Thanks for any input John Hodgson ------------------------------------- code/selected output ----------------- library(metafor) ## Set up data (from Lenters et al A Meta-analysis of Asbestos and Lung Cancer... ##