similar to: replicates in repeated ANOVA

Dear Group: I am working with a data frame containing 316 rows of individuals with 79 variables. Each of these 79 variables have values that range between -4 to +4, and I want to subset this data frame so that in the resulting new dataframe, values of _all_ of these variables should range between -3 and +3. Let's say I have the following dataframe (it's a toy example with 4 individuals

Dear all, I am estimating a mixed-model in Ubuntu Raring (13.04¸ amd64), with the code: fm0 <- lme(rt ~ run + group * stim * cond, random=list( subj=pdSymm(~ 1 + run), subj=pdSymm(~ 0 + stim)), data=mydat1) When I check the approximate variance-covariance matrix, I get: > fm0$apVar [1] "Non-positive definite

Hi, R 2.5.0 isn't auto-completing paths properly as it used to. E.g. suppose I have: > dir("CEL/choe") [1] "chipC-rep1.CEL" "chipC-rep2.CEL" "chipC-rep3.CEL" "chipS-rep1.CEL" [5] "chipS-rep2.CEL" "chipS-rep3.CEL" Now if I do: ReadAffy("CEL/choe/ch<tab> # => ReadAffy("CEL/choe/chip

I've been running a glmer logit on a very large data set (600k obs). Running on a 10% subset works correctly, but for the complete data set, R completes apparently without error, but does not display the results. Given these jobs take about 200 hours, it's very hard to make progress by trial and error. I append the code and the sample and complete output. As is apparent, I upgraded R

Hi R Users, I do have very big data sets and wanted to run some of the analyses many times with randomization (1000 times). I have done the analysis using an example data but it need to be done with randomized data (1000 times). I am doing manually for 10000 times but taking so much time, I wonder whether it is possible to perform the analysis with creating a loop for many replicated datasets?

Hi, I'm generating the name of the variable with paste function and then using that variable name further to get the specific position value from the data.frame, here is the snippet from my code: modelResults <- extractModelParameters("C:/PilotStudy/Mplus_Input/Test", recursive=TRUE) #extractModelParameters reads all the output files from the Test folder and create the

List, I want to reshape my data, but I'm not sure how to do it... it might be a simple task, but don't know which package does this. "occ.data" (see below) is how my original data are arranged, and I know that with melt() I can reshape it like "y" (see below). However, I just want to build a matrix like the "y" matrix, but with only 2 dimensions. Something

Hi all, I have a rather peculiar dataset that I'm not sure how to model properly. This is data from an instrument that measures the size of particles but instead of giving a continuous value, it generates a "histogram" of the counts for a particular bin size. So the data looks like this: Condition 1 Condition 2 Dimension Rep1.A Rep1.B

I am trying to merge two data frames, but one of the column headings are different in the two frames. How can I rjoin or rbind the tho frames? Johnny # Generate 2 blocks by confounding on abc d1 <- conf.design(c(1,1,1), p=2, block.name="blk", treatment.names = c("A","B","C")) d2 <- conf.design(c(1,1,1), p=2, block.name="blk",

Greetings. How can I insert gridlines in the following density plot call? Must one compose a panel function? 'data.frame': 46 obs. of 2 variables: $ fallrates: num 5.2 7.1 7.1 9.8 3.7 7.5 5 6.2 1.5 2.9 ... $ prepost : Factor w/ 2 levels "post","pre": 2 2 2 2 2 2 2 2 2 2 ... library(lattice) densityplot(~fallrates, groups = prepost,

Hi I compouted a multiple linear regression with repeated measures on one explanatory variable: BOLD peak (blood oxygenation) as dependent variable, and as independent variables I have: -age.group (binaray:young(0)/old(1)) -and task-difficulty measured by means of the reaction-time 'rt'. For 'rt' I have repeated measurements, since each subject did 12 different tasks. -> so

Hello R experts: When I tried to read my data into R, it does not take # sign A subset of Exp.txt is: Experiment name assay id Varname (A1)DBA TPA 6h/DBA Acetone rep1(A1) #3 4090 A90C1 (A2)DBA TPA 6h/DBA Acetone rep2(A2) #3 4091 A91C1 The command is: Exp <- read.delim2("Exp.txt",check.names=F,as.is=T) It is excuted but gave me all the NAs. Can you all drop me a hint? Thanks

On 8/25/2017 12:56 AM, Gionatan Danti wrote: > > >> WK wrote: >> 2 node plus Arbiter. You NEED the arbiter or a third node. Do NOT try 2 >> node with a VM > > This is true even if I manage locking at application level (via > virlock or sanlock)? We ran Rep2 for years on 3.4.? It does work if you are really,really? careful,? But in a crash on one side, you might

Il 25-08-2017 21:48 WK ha scritto: > On 8/25/2017 12:56 AM, Gionatan Danti wrote: > > > We ran Rep2 for years on 3.4.? It does work if you are really,really? > careful,? But in a crash on one side, you might have lost some bits > that were on the fly. The VM would then try to heal. > Without sharding, big VMs take a while because the WHOLE VM file has > to be copied over.

the glusterfs 3.0.X crashed on Fedora 12, it got buffer overflow, seems fine on Fedora 11 Name : fuse Arch : x86_64 Version : 2.8.1 Release : 4.fc12 Name : glibc Arch : x86_64 Version : 2.11.1 Release : 1 complete log: ====================================================================================================== [root at test_machine06 ~]# glusterfsd

Hi Jon, your patches are malformed because (presumably) your email client wrapped this lines. Could you please send these as a unified diff ("diff -u"), and send them in attachments, rather than as a copy-and-paste? Thanks, -- Peter Jon Gough wrote: > > Peter, > Here are the files I have worked on. I hope I have diff'd them > correctly. I have not touched the

Hi, I need to resample characters from a dataset that consists of an extremely long string that is written over hundreds of thousands of lines, each of length 50 characters. I am currently doing this by first inserting a space after each character in the dataset and then using the following commands: y <- as.matrix(read.table("data.txt"), stringsAsFactors=FALSE) bstrap <-

This is the specific error messsage from R CMD check --as-cran Error in .check_ncores(length(names)) : 16 simultaneous processes spawned Calls: prepost -> makeCluster -> makePSOCKcluster -> .check_ncores Execution halted Thanks, Ravi ________________________________ From: Ravi Varadhan Sent: Saturday, July 1, 2023 1:15 PM To: R-Help <r-help at r-project.org> Subject: Number

Dear List, After running a compound symmetric model using gls, I realized that the default contrasts were not the ones that made the most sense given the biological relationships among the factor levels. When I either changed the factor levels to re-arrange the order they occur in the gls model (not shown below) OR specifically change the contrasts I get the exact same estimates for the

Hi all. I have a re-occuring typical problem that I don't know how to solve efficiently. The situation is the following: I have a number of data-sets (A,B,C,...) , consisting of an identifier (e.g. 11,12,13,...,20) and a measurement (e.g. in the range 100-120). I want to compile a large table, with all availabe identifiers in all data-sets in the rows, and a column for every