similar to: Efficient ways of finding functions and Breslow-Day test for homogeneity of the odds ratio

Breslow-Day test A statistical test for the homogeneity of odds ratios. Homogeneity In <javascript:void(0);> systematic reviews homogeneity refers to the degree to which the results of studies included in a review are similar. "Clinical homogeneity" means that, in studies included in a review, the participants, interventions and outcome measures are similar or comparable.

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

Dear R Users, I'm looking for a package that allows to test hypothesis about a homogeneity of odds ratio in k 2x2 tables. I know that Breslow-Day is suitable but does anybody could me point out a package? I found diffR, but as far as I see this package is for IRT theory. Best, Robert

Hi all, I want to know how to perform the test Breslow-Day test for homogeneity of odds ratios (OR) stratified for svytable. This test is obtained with the following code: epi.2by2 (dat = daty, method = "case.control" conf.level = 0.95, units = 100, homogeneity = "breslow.day", verbose = TRUE) where "daty" is the object type table svytable consider it, but

Hello everyone, Does anyone know if I can do Breslow Day Test for the homogeneity of odds ratio in R? Thanks! - Jacqueline

Hi all, The survivals functions can be tested by the Log-rank test and others, for example the Gehan-Breslow. The graham breslow work with the alpha values. But I don't know how is the Gehan-Breslow test with R. Somebody know a type function?.. or other suggestions? Any help will be really appreciated Jos? Bustos Marine Biologist Master Apllied Stat Program University of Concepci?n

Dear R-users, I am checking the proportional hazard assumption of a cox model for a given covariate, let say Z1, after adjusting for other relavent covariates in the model. To this end, I fitted cox model stratified on the discrete values of Z1 and try to get beslow estimator for the baseline cumulative hazard function (H(t)) in each stratum. As far as i know, if the proportionality assumption

Hi, does anyone know of a function to calculate odds ratios in multiway tables (stratified) (+ the other usual statistics involved) i mean: say we have a table r*c*d, For every d (depth) we have a r*c table, and in this table the odds ratio's are calculated for every 2*2 subtable in it. logically this function would look like): ORs(multiwaytable) or ORs(data$var1r,data$var2c,data$var3d)

this may be slightly off-topic, as it doesn't pertain directly to the R application, but some of the documentation. when reading R's fullrefman.pdf (available from http://cran.r-project.org/doc/manuals/fullrefman.pdf) in Mac OS X's preview.app (version 4.1, on Mac OS 10.5.x), if i try to do a keyword search within the document, the indexing step freezes about 2/3 the way through the

Hi List. It may be a very simple question, but I couldn’t find an answer on the internet. Which function (maybe in a specific package) would I use to perform a Cochran C Test for Homogeneity of Variances? Stats package have the mantelhaen.test, but I’m “almost sure” that It’s not what I want, it’s probably the Cochran Q Test. So, any ideas? Thank you for the pacience.

Hi R users I have serveral binary variables (e.g., X1, X2, X3, X4, X5, X,6, and X7) and one continuous variable (e.g., Y1). I combined these variables using data.frame() mydata <- data.frame(X1,X2,X3,X4,X5,X6,X7,Y1) after that, I sorted this data.frame rank.by.Y1<-order(mydata[,8]) sorted.mydata<-mydata[rank.by.Y1,] after that, I replaced Y1's values with values ranging from 1

I partly answered my question since independence_test() function in coin package apparently do Cochran-Armitage trend test just like Eric Lecoutre's function tabletrend() - slightly modified here: > independence_test(pheno ~ geno, data = dat2, teststat = "quad", scores = list(geno = c(0, 1, 2))) Asymptotic General Independence Test data: pheno by groups 1 < 2

Hello, I was using the mantelhaen.test function (2x2 J tables for conditional independence testing). I noticed that the option for the continuity correction (correction=T or correction=F) sometimes made a difference while sometimes it did give the same results regardless of correction=T or correction=F. Does the continuity correction apply only in certain cases or in certain strata with some

Full_Name: Chien-yu Peng Version: 2.0.1 OS: Windows XP Professional Submission from: (NULL) (140.109.72.181) Dear all: Although I don't know you, I am thankful for your help. When I use the function mantelhaen.test for R x C x K (R, C > 2) table, the output is not the same as SAS's. I don't know that the result consist with one of SAS's. But it works correctly for 2

Hi, Found no measure of association or correlation for 2x2 contingency tables in fullrefman.pdf or google. Can someone point to a package that implements such calculations? Thanx. -- Alexandre Santos Aguiar - consultoria para pesquisa em sa??de - R Botucatu, 591 cj 81 tel 11-9320-2046 fax 11-5549-8760 www.spsconsultoria.com

Hi, All! To calculate Levene's Test for Homogeneity of Variance I use R Commander, and this is the output: > levene.test(Dataset$age, Dataset$sex) Levene's Test for Homogeneity of Variance Df F value Pr(>F) group 1 0.8739 0.3567 33 I am not sure what means "Pr(>F)"? Can anyone explain/translate this? Regards, Iurie Malai Department of Psychology and

According to the MikTex bug reports [1], MikTex 2.9 has removed texi2dvi.exe last week (on 2015-09-29) as "it was not compatible (anymore) with the original shell script texi2dvi (GNU Texinfo)." I found this out the hard way as I just (unknowingly) updated MikTex this evening, and then, while building R-devel_2015-10-08 on Windows7 64bit using the Rtools 3.3 toolchain (4.9.3 branch), had

I am testing the homogeneity of variances via bartlett.test and fligner.test. Using the following example, how should I interpret the p-value in order to accept or reject the null hypothesis ? set.seed(5) x <- rnorm(20) bartlett.test(x, rep(1:5, each=4)) Bartlett test of homogeneity of variances data: x and rep(1:5, each = 4) Bartlett's K-squared = 1.7709, df = 4, p-value =

Has the Levene test of homogeneity of variance been implemented in any library in R? Thanks, Maurice Haynes National Institute of Child Health and Human Development Child and Family Research Section 6705 Rockledge Drive Bethesda, MD 20892 Voice: 301-496-8180 Fax: 301-496-2766 E-Mail: mh192j at nih.gov

Dear all, I'm a beginner of R and I need to carry out some three-way mixed ANOVAs. Following examples at http://personality-project.org/r/r.anova.html, I managed to get the ANOVA part, but I don't know how can I check data normality and homogeneity of variance in R (since they're the required assumptions of ANOVA analysis). Are there any special command/packages? Could anyone give me