similar to: by group testing

Dear all, I am new R user and I am sure that this question has been asked quite often and I have also googled it and read about it! I understood that in order to read excel sheet into R you need to open it and saved it as csv or text, is this true? or you can use read.delim2 and read.csv2 to do this without the following error > dat <- read.csv2(file="C:\\Dokumente und

Dear all, What is the right test to test whether the median of two groups are statistically significant? Is it the wilcox.test, mood.test or the ks.test? In the text book I have got there is explanation for the Wilcoxon (Mann Whitney) test which tests ob the two variable are from the same population and also ks.test! Regards, Cheba [[alternative HTML version deleted]]

Dear R people, Is it possible to save three data sets in an R object and to call each data from this object independently! Regards, Cheba [[alternative HTML version deleted]]

Hello, I have to compute the pooled z-value and I would like to know which way is more appropriate b <- c( -0.205,1.040,0.087) s <- c(0.449,0.167,0.241) n <- c(310, 342, 348) z <- b/s Z <- sum(z)/sqrt(length(n)) P <- 2*(1-pnorm(abs(Z))) P w <- sqrt(n) Zw <- sum(w * z)/sqrt(sum(w^2)) Pw <- 1 - pchisq(Zw * Zw, 1) Pw Many thanks in advance, Cheba [[alternative HTML

Hello, I am using library(gplots) to do something like data(state) x1 <- state.area/10000 x2 <- x1+round((rnorm(length(state.area),3,3))) plotmeans(x1 ~ state.region) Is it possible to plot x2 to x1 in the same graph, something like: linesmeans(x2 ~ state.region) Best wishes, Cheba [[alternative HTML version deleted]]

Dear all, I am doing library(survival) fit <- coxph(Surv(futime,fustat) ~ rx, ovarian) plot(survfit(fit,newdata=ovarian),col=c(1,2)) legend("bottomleft", legend=c("rx = 0", "rx = 1"), lty=c(1,2),col=c(1,2)) Is this correct to compare these two groups? Is the 0.31 the p-value that the median f two groups are equal Why lty does not work here? Many thanks

Dear all, I have a four variable: Stuy.Name, OR, 95%LCI and 95%UCI and I would like to create a meta analysis plot. I can't use meta.MH function in metaplot because I do not have n.trt, n.ctrl, col.trt, col.ctrl are not available! Is there an alternative way to do it? Many thanks in advance, Cheba [[alternative HTML version deleted]]

Hi all, from http://docs.puppetlabs.com/guides/language_tutorial.html this syntax should be ok: file { [ ''foo'', ''bar'', ''foobar'' ]: owner => root, group => root, mode => 600, } I''ve this in my code: file { [ ''/software/atlas'' , ''/software/cms'' ,

Hello R users I have a question with Kaplan-Meier Curve with respect to my research. We have done a retrospective study on fillings in the tooth and their survival in relation to the many influencing factors. We had a long follow-up time (upto 8yrs for some variables). However, we decided to stop the analysis at the 6year follow up time, so that we can have uniform follow-up time for all the

Hi, I have a pretty simple problem. Here is the code: dat1=complete(dat.mice,1) dat2=complete(dat.mice,2) dat3=complete(dat.mice,3) dat4=complete(dat.mice,4) dat5=complete(dat.mice,5) dat6=complete(dat.mice,6) dat7=complete(dat.mice,7) dat8=complete(dat.mice,8) dat9=complete(dat.mice,9) dat10=complete(dat.mice,10) dat11=complete(dat.mice,11) dat12=complete(dat.mice,12)

I am running a simulation many times changing one parameter each time and recording the outcome. I have to produce a plot to make a sense of the bunch of numbers I get from every run. My problem is to insert a multi-line text to keep track of which result correspond to which parameter values. A legend does not work in this case because I will plot 2 variables and the corresponding experimental

Sorry, I was not clear enough. The reason I want to use mice::mice() rather than library(mice); mice() is that I want to call it from my own package. But the reprex works from the command line as well, straight after launching R: mice::mice(airquality) #> Error in check.method(setup, data): The following functions were not found: mice.impute.pmm, mice.impute.pmm The mice.impute functions

Hello, I tried intalling mice package and got the following error: * installing *source* package ?mice? ... ** package ?mice? successfully unpacked and MD5 sums checked ** libs g++ -I/usr/local/lib/R/include -DNDEBUG -I"/home/djj/R/x86_64-pc-linux-gnu-library/3.4/Rcpp/include" -I/usr/local/include -fpic -g -O2 -c RcppExports.cpp -o RcppExports.o g++ -I/usr/local/lib/R/include

IIUC, this would be an isssue with MICE (or rather "mice"), which isn't Ole's. It could be a namespace issue, but it could also be that some start-up code is not executed if library() is bypasses (see .onAttach et al.). -pd > On 4 Oct 2017, at 17:00 , Michael Dewey <lists at dewey.myzen.co.uk> wrote: > > Dear Ole > > One of the experts may be able to

I want to call the mice function from the MICE package from my own package. However I run into this issue, which can be reproduced on the command line: mice::mice(airquality)#> Error in check.method(setup, data): The following functions were not found: mice.impute.pmm, mice.impute.pmm I have no problems when doing library(mice) mice(airquality) Is this a bug or am I missing something?

> On Nov 15, 2017, at 1:08 AM, Jeremie Juste <jeremiejuste at gmail.com> wrote: > > > > Hello, > > I tried intalling mice package and got the following error: > > * installing *source* package ?mice? ... > ** package ?mice? successfully unpacked and MD5 sums checked > ** libs > g++ -I/usr/local/lib/R/include -DNDEBUG

Dear Ole One of the experts may be able to diagnose this without extra information but I suspect you have not got the right magic in your NAMESPACE file in your package. You may need to re-read section 1.5.1 of the Writing R extensions manual. Michael On 04/10/2017 13:47, Ole H?st wrote: > I want to call the mice function from the MICE package from my own package. > However I run into

#I wish to create a "list of three dataframes" ("results2") from a "list of two dataframes" (temp) and a dataframe ("c")? #Please advise. a <- data.frame(x=c(1,2,3),y=c(5,7,9)) b <- data.frame(x=c(2,4,7,9),y=c(2,3,5,4)) c <- data.frame(x=c(22,34,7,9),y=c(52,63,5,4)) results1 <- list(a,b,c) #what I want #but this is how I need to get there

The concrete problem is that I am refereeing a paper where a confidence interval is presented for the risk ratio and I do not find it credible. I show below my attempts to do this in R. The example is slightly changed from the authors'. I can obtain a confidence interval for the odds ratio from fisher.test of course === fisher.test example === > outcome <- matrix(c(500, 0, 500, 8),

Just to inform: I posted that before in R-sig-ecology but as it might be interesting also for other useRs, I post it also to the general r-user list: Hello Alexandre, thank you very much. I also found another way to extract summarizing information from lm results over e.g. 1000 repeated model runs: results2 <- t(as.data.frame(results)) summary(results2) Although some questions popped up in