similar to: [Fwd: Trend test and test for homogeneity of odd-ratios]

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 very new to R. So, pardon my dumb question. I was trying to write my own function to run a different model (perform an ordered logistic regression) using the example in website http://pngu.mgh.harvard.edu/~purcell/plink/rfunc.shtml But R returns a error `R Error in eval(expr, envir, enclos) : object 's' not found' when I run it. What am I doing wrong here? Here's

Dear R-enthusiasts, I am trying to do a Cochran-Armitage test for trend in R. After consulting google I found Torsten Hothorn's remark that the 'coin' library could be used. lungtumor <- data.frame(dose = rep(c(0, 1, 2), c(40, 50, 48)), tumor = c(rep(c(0, 1), c(38, 2)), rep(c(0, 1), c(43, 7)),

Hello, When I try: geno <-read.table("2500.geno.tab",header=TRUE,sep="\t",na.strings=".",quote=" ",comment.char="",colClasses=c("factor"),nrows=2501) I get, after hour(s) of work: Error: cannot allocate vector of size 9 Kb I have: Rgui.exe --max-mem-size=3Gb and multi(0)disk(0)rdisk(0)partition(1)\WINDOWS="Microsoft

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

Dear all a couple of months ago i've found threads regard test that verify AnOVa assumption on homogeneity of variances. Prof. Ripley advice LDA / QDA procedures, many books (and many proprietary programs) advice Hartley's F_max, Cochran's minimum/maximum variance ratio (only balanced experiments), K^2 Bartlett's test, Levene's test. Morton B. Brown and Alan B. Forsythe in a

Hello, When programming it is better to use dat[["variable"]] than dat$variable. So your code could be pfas.pheno[[cat.var]] <- NA pfas.pheno[[cat.var]][pfas.pheno[,i] <= quantile(pfas.pheno[,i],0.25, na.rm =T)] <- 0 etc. Untested. Hope this helps, Rui Barradas On 4/19/2018 7:20 PM, Ding, Yuan Chun wrote: > Hi All, > > I want to create a categorical variable,

> On Apr 19, 2018, at 11:20 AM, Ding, Yuan Chun <ycding at coh.org> wrote: > > Hi All, > > I want to create a categorical variable, cat.pfoa, in the file of pfas.pheno (a data frame) based on log2pfoa values. I can do it using the following code. > > pfas.pheno <-within(pfas.pheno, {cat.pfoa<-NA > cat.pfoa[pfas.pheno$log2pfoa

Hi All, I want to create a categorical variable, cat.pfoa, in the file of pfas.pheno (a data frame) based on log2pfoa values. I can do it using the following code. pfas.pheno <-within(pfas.pheno, {cat.pfoa<-NA cat.pfoa[pfas.pheno$log2pfoa <=quantile(pfas.pheno$log2pfoa,0.25, na.rm =T)]<-0 cat.pfoa[pfas.pheno$log2pfoa >=quantile(pfas.pheno$log2pfoa,0.75, na.rm =T)]<-2

> On Apr 19, 2018, at 1:22 PM, David Winsemius <dwinsemius at comcast.net> wrote: > > >> On Apr 19, 2018, at 11:20 AM, Ding, Yuan Chun <ycding at coh.org> wrote: >> >> Hi All, >> >> I want to create a categorical variable, cat.pfoa, in the file of pfas.pheno (a data frame) based on log2pfoa values. I can do it using the following code.

I am trying to find a convenient way to control line colors when printing from a for loop using the lines command. Right now I have solved this by creating a colors vector that is refered to in the loop with index. However, the colors choosen here are just 1,2,3,4,5... I would like to get colors from the col = rainbow(x) that you can use in plot() and set the to be my number of lines (I think

Anyone know if coin can run a permutation test based on a (user-defined) statistic other than the mean difference? The function independence_test does the permutation t-test via difference in means. I'm wondering if it's possible to use independence_test to run a permutation test for some other statistic than the difference in means. For example, I'd like to run a permutation test

Dear List Members, I have encountered two problems when using the step function to select models. To better illustrate the problems, attached is an R image which includes the objects needed to run the code attached. lm.data.frame have factor variables with 3 levels. The following run shows the first problem. AICs (* and **) are different. I noticed that the Df for rs13482096:rs13483699 is 4,

Dear List Members, I have encountered two problems when using the step function to select models. To better illustrate the problems, an R image (step.add1.test.RData) which includes the objects needed to run the code (step.add1.test.R) can be found at www.biostat.wisc.edu/~pwang/r-help/<http://www.biostat.wisc.edu/%7Epwang/r-help/> lm.data.frame have factor variables with 3 levels. The

Dear R users, This command works (calling a programm -called whap- with file specifiers etc.): >system('cmd /c "c:\\pheno\\whap --file c:\\pheno\\smri --alt 1 --perm 500"', intern=TRUE) Now I need to call it from a loop to replace the "1" by different number, however I get lost using the quotes: I tried numerous versions of: >i<-1

I am receiving the above error ( full r session output below) the script runs OK in windows. and "genotypes" and "ploidy" are both correct arguments any suggestions would be most welcome Nevil Amos MERG/ACB Monash University School of Biological Sciences > library(Geneland) Loading required package: RandomFields Loading required package: fields Loading required

Hi all, Here is my problem: I performed bioassays using a unique insecticide on 9 different genotypes and got their mortality depending on the dose of insecticide used. Now, I want to see wether some genotypes are different or not in their responses to insecticide. My problem is that I have up to four replicates for some genotypes, but only one for other... Due to this unbalanced design, I

Dear R helpers, I am trying to understand how to use the independence_test function in the coin package. I think I suffer from a misunderstanding about what the package does. Either that or I do not understand how to use it properly. Specifically, I cannot understand if I can test independence of arbitrary statistics. Take the following example: set.seed(10) d <- data.frame(y = c(rnorm(10,

I am trying to do this, but it won't work: > library(lattice) > elemconc = data.frame(expand.grid(id=1:20, geno=c('exp', 'wt'), region=c('cor', 'cr', 'spine'), elem=c('fe', 'cu', 'zn')), conc=rnorm(360, 10)) > elemconc$geno = factor(elemconc$geno) > elemconc$region = factor(elemconc$region) > for (i in

I am trying to use the function 'filter.NA=TRUE' in Geneland. The function appears to be set on TRUE by default, as it appears as TRUE in the 'parameter.txt' file output and hence I do not need to enter the function per se (as it is an 'Unused argument otherwise') . Hence all my missing data (individuals that I have not yet scored at that specific loci) are scored as