similar to: Package or packages for randomization in a clinical trial

Hi, I’m new to R (just installed today) and I’m trying to figure out how to do stratified randomisation using it. My google search expedition has lead me to believe that blockrand package will most probably be the answer to it. I’ve played around with blockrand for awhile and tried the sample code: library(blockrand) ##stratified by sex male <- blockrand(n=100,

Hi, I am very new to R. Just started yesterday. I have to generate a sequence of 40 random treatments using permuted block randomization with a block size of 8. Then I have to plot moving averages for the resulting sequence. I have tried the sample function but I dont know if wht i did is right or not > sample(c(1,1,1,1,2,2,2,2),8) Any ideas please? -- Ayesha Khan MS Bioinformatics Dept. of

Hello R people, I am looking to pay someone to help write some R code. Inputs: Study identifier: ID Number for the study, each ID number is for one study only each block set should only be used for that study. This will require that you store the results from the blocks someplace on the file system. Trait #1: dichotomous rural / urban Trait #2: dichotomous sick / healthy Assignment Ratio:

Dear all, Can anybody tell me how to export a 3d figure made with the plot3d function? I'm careless about whether it's still interactive or not in another format, as long I can get it out of R. Thanks! Alejandro Gonz?lez Departamento de Biodiversidad y Conservaci?n Real Jard?n Bot?nico Consejo Superior de Investigaciones Cient?ficas Claudio Moyano, 1 28014 Madrid, Spain Tel +0034

Hello, I will be very obliged if someone can help me with this statistical R problem: I am trying to do a Pearson correlation on my datasets X, Y with randomization test. My X and Y datasets are pairs. 1. I want to randomize (rearrange) only my X dataset per row ,while keeping the my Y dataset as it is. 2. Then Calculate the correlation for this pair, and compare it to your true

Hello, I have what I suspect might be an easy problem but I am new to R and stumped. I have a data set that looks something like this b<-c(2,3,4,5,6,7,8,9) x<-c(2,3,4,5,6,7,8,9) y<-c(9,8,7,6,5,4,3,2) z<-c(9,8,7,6,1,2,3,4) data<-cbind(x,y,z) row.names(data)<-c('a','b','c','d','e','f','g','h') which gives: x y z

By randomization of functions I mean the manner in whch they are called , so that has to do with address.I wish to randomize the order of calls made to functions when a program is run. Reid Spencer <reid at x10sys.com> wrote:Can you explain a little bit more about what you mean by "randomize" functions or global variables? What aspect of them do you want to randomize? Their

Hello dear R-help group. My task looks simple, but I can't seem to find a "smart" (e.g: non loop) solution to it. Task: I wish to randomize a data.frame by one column, while keeping the inner-order in the second column as is. So for example, let's say I have the following data.frame: xx <-data.frame(a= c(1,2,2,3,3,3,4,4,4,4) , b =

On Thu, Jun 02, 2005 at 02:12:22PM -0700, Tanu Sharma wrote: > By randomization of functions I mean the manner in whch they are > called , so that has to do with address.I wish to randomize the order > of calls made to functions when a program is run. How would you "randomize the order of calls made to functions when a program is run" without changing the semantics of the

Is anybody using R to do analysis of clinical trial datasets that have been put in the public domain (which are super hard to find). Not only a single data table, but the actual database, with a handful of data tables with one-to-one or many-to-one relationships? [ For example, "Adverse Events" and "Patient Info" are two datasets with a many-to-one relationship, the

Dear all, I am happy to announce that {simtrial} is now on CRAN (https://cran.r-project.org/package=simtrial). simtrial is a fast and extensible clinical trial simulation framework for time-to-event endpoints. This release brings a new tabular data processing engine powered by data.table for 3x to 5x faster simulations, a new parallelization adaptor with %dofuture%, a refreshed API that aligns

Dear all, I am happy to announce that {simtrial} is now on CRAN (https://cran.r-project.org/package=simtrial). simtrial is a fast and extensible clinical trial simulation framework for time-to-event endpoints. This release brings a new tabular data processing engine powered by data.table for 3x to 5x faster simulations, a new parallelization adaptor with %dofuture%, a refreshed API that aligns

On Sat, Jun 10, 2017 at 4:09 PM, Davide Italiano <davide at freebsd.org> wrote: > On Tue, Jun 6, 2017 at 10:55 AM, Stephen Crane via llvm-dev > <llvm-dev at lists.llvm.org> wrote: >> This RFC describes pagerando, an improvement upon ASLR for shared >> libraries. We're planning to submit this work for upstreaming and >> would appreciate feedback before we get

This RFC describes pagerando, an improvement upon ASLR for shared libraries. We're planning to submit this work for upstreaming and would appreciate feedback before we get to the patch submission stage. Pagerando randomizes the location of individual memory pages (ASLR only randomizes the library base address). This increases security against code-reuse attacks (such as ROP) by tolerating

On Mon, Jun 12, 2017 at 1:03 PM, Stephen Crane <sjc at immunant.com> wrote: > I don't have performance measurements for the new LTO version of > pagerando yet. I'll definitely be thoroughly measuring performance > once the current prototype is finished before moving forward, and will > post results when I have them. > > I'm definitely curious about your work

Daniel, When Group is entered as a factor, and the factor has two levels, the ANOVA table gives a p value for each level of the factor. What I am looking for is the omnibus p value for the factor, i.e. the test that the factor (with all its levels) improves the prediction of the outcome. You are correct that normally one could rely on the fact that the model

Hi, I have a series of id's with multiple visits and questionnaire scores. This is a clinical trial that will be analyzed using the last observation carried forward method. In other words, in order to comply with intent to treat analysis when many subjects withdraw, data points for the last visit must be generated and filled in with the last observation. The ultimate goal is to tabulate the

My wife has been using a diagnostic from Manley (1991; "Randomization and MonteCarlo Methods in Biology") that compares a normal multiple regression's performance with that using random predicted variables. Is there something like this already available in R? If not, the "boot" package looks like a good place to start looking for methods, no? Thanks in advance Bruce

Hello everyone, I am trying to use the 'find.BIB' function to construct a balanced incomplete block design. When I ran the example given in the help file (find.BIB(10,30,4)), I obtained the following error message: Error in optBlock(~., withinData = factor(1:trt), blocksize = rep(k, b)) : object ".Random.seed" not found I investigated what the optBlock

Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working