search for: dunner

Hello all, kind regards, I have imported a data.frame from SPSS using "foreign":read.spss but unfortunately it is reading dates in a way neither R nor myself can understand. > book$DATE [1] 13502246400 13443321600 13477795200 13472956800 13501728000 13445395200 13501382400 13502851200 13444185600 13461465600 13457232000 [12] 13458096000 13432435200 13431484800 13495334400

I have written a function to emulate minitab's QQ plotting output (with SW test and AD test results on the graph): mtab.norm<-function(x) { library(nortest) library(lattice) x<-as.numeric(x) x<-as.vector(x) plot.ht<-4.6 plot.wd<-4.6 pt.ht=plot.ht/5 txt.sz<-(plot.ht/7.5) X11(width=plot.wd, height=plot.ht, bg='gray96') qqplot(x, pch=16, cex=pt.ht,

Hello, and thanks for your time I'm trying to extract standard errors to produce confidence intervals from a multivariable coxme model object so I can write a function that will print a summary for some reproducible research. As far as I can glean, the SE is produced on-the-fly by the print method. I'll dig into the source code if I have to, but I'd rather not have to. Any help

Hello all, thanks for your time and patience. I'm looking for a method in R to analyse the following data: Time to waking after anaesthetic for medical procedures repeated on the same individual. > str(mysurv) labelled [1:740, 1:2] 20 20 15 20 30+ 40+ 50 30 15 10 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:2] "time" "status" -

Please help with this error message drugbook is an 885 x 32 dataframe >names(drugbook) [1] "DRUG1" "DRUG2" "DRUG3" "DRUG4" "DRUG5" [6] "DRUG6" "DRUG7" "DRUG8" "DRUG9" "DRUG10" [11] "DRUG11" "DRUG12"

Hi all, thank you for your patience. I am dealing with a large dataset detailing patients and medications Medications are hard to code, as they are (usually) meaningless unless matched with doses. I have a dataframe with vectors (Drug1, Drug2..... Drug 16) and individual patients are represented by rows. The vectors are actually factors, with 100s of possible levels (all the drugs the patient

Thanks all for your help. I fear text mining is an abstract little corner of "R". I have imported 3228 text (.txt) files, each a news story, into R using [tm]: textd <- Corpus(DirSource("other/docs"), readerControl = list(reader =readPlain)) I can pre-process each individual document using tolower(textd[[1]]) however, when I try to run tmTolower() I get a no such command

Hello all, thanks in advance for the trouble. I can't reshape a particular large data.frame. I have used melt and reshape successfully before, alot. I am trying to go from wide to long format. I wish to separate The named variables below into 3 groups : SYST, DIAST and PULSE, and have them vary according to their timepoint: BAS, PRE, POST, INI ..... 240. Currently: > dim(book) [1] 885

Hello I am using glmmBUGS to fit a multilevel model. Treatments are nested in Course are nested in Patients. The predicted variable in total EEG duration. The predictors are: at the observation level : Medication dose at the Course level: Weight in KG and Age at the Patient level: Weight in KG and Age I am trying to fit a multilevel model as in lmer, but in BUGS. Here is an example of the

R programming question, not machine learning, although that's the content. Apologies to all for whom the following code is eye-burning. I am using foreach() to run a simulation on a randomForest model (actually conditional randomForest ... "party" package). The simulation is in two dimensions. examining how "mtry" and "ntrees" are related in terms of predictive