similar to: Extracting labels for residuals from lme

Dear R helpers, I would like to ask why polr occasionally generates results that look very odd. I have been trying to compare the power of proportional odds logistic regression with the Wilcoxon test. I generated random samples, applied both tests and extracted and compared the p-values, thus:- library(MASS) c1=rep(NA,100); c2=c1 for (run in 1:100) { dat=c(rbinom(20,12,0.65),rbinom(20,12,0.35))

Oh dear - I joined the R help mailing list last week, in order to ask a specific question. I did not realise that I would start to receive all e-mails to and from the mailing list. Is there a way of letting me receive only the answers to my own questions? If not, then can you remove me from the mailing list? Thanks, Jonathan Williams Jonathan Williams OPTIMA Radcliffe Infirmary Woodstock Road

I am trying to analyse recurrent failure times using survfitr from the survrec package. To do this, I need to "Create a survival recurrent object" using Survr. But, when I do this, I get an error "Error in Survr(r1d[, 1], r1d[, 5], r1d[, 6]) : data doesn't match". Here, r1d[,1] is the identifier for each case, r1d[,5] is the time of recurrence, r1d[,6] is the status

Hi Helpers, Does anyone know how to read jpeg, bmp or png files into R? I have some photos of brain scans and I want to quantify some aspects of their size. I might be able to do this with the 'locator' function, if I could figure out how to read the files in and make them into an image that I can display on the R Windows device. I have experimented with readBin, using a simple

Jonathan, Try making a list instead of an array. See ?list. Also, did you look into random forests? I'm not sure what you want to do, but there might be methods there to do some of the work for you. Sean On 3/19/04 1:12 PM, "Jonathan Williams" <jonathan.williams at pharmacology.oxford.ac.uk> wrote: > I would like to collect the trees grown by rpart fits in an array,

Dear R helpers, I have a curious problem, which is that a program I have written in R crashes R, unpredictably. When I say that the program crashes R, I mean that it causes R to terminate, completely. But, the operating system (Windows) continues OK. The program loops around a randomForest regression. I am trying to use randomForest to predict the diagnosis for a set of patients with dementia. I

Jonathan, Is there any possibility for you to send me the data, and/or the code? I and others have seen similar problems before, but not reproducible on the current version, at least on the NT and Linux boxes that I have access to. As Thomas said, it's difficult to nail these kinds of problems. Having reproducible data and code, at least, can help. (It's no help that I'm no expert

I have a time series of data from an electroencephalogram (EEG). I wish to filter the data to get rid of 50Hz mains 'hum'. I have 'designed' a combination bandpass and notch filter using a web- site. The site returns the filter in "ANSI C" source code. It is:- /* Digital filter designed by mkfilter/mkshape/gencode A.J. Fisher Command line:

Is there a good way in R to impute values which exist, but are less than the detection level for an assay? Thanks, Jonathan Williams OPTIMA Radcliffe Infirmary Woodstock Road OXFORD OX2 6HE Tel +1865 (2)24356

Dear R helpers, I wish to use the "sum" operator for each row of a data frame. However, it appears that the operator acts on the entire data frame, over all columns. What is the best way to obtain row- wise operation? The following code shows my attempts so far, and their problems:- test1=array(rbinom(120,1,0.5),c(20,3)) test1[,3]=NA sum(test1[,1:2]) test1[,3][sum(test1[,1:2])>=2]=1

Dear R-helpers, I am having difficulty making R plot only integer labels on the x-axis of a simple graph. I want to plot the median values of a score on each of three occasions. Non-integer occasions are impossible. But, R keeps labelling the x-axis with half-occasions, despite my attempts to stop this using the "xaxs" and "xaxp" parameters of 'plot'. p1=c(1,2,3);

I am having great difficulty plotting what should be a simple graph. I have measured 1 'y' and 5 'x' variables in each of two groups. Linear regression shows significant differences in the slopes of the regression for each 'x' variable between the two groups. All that I want to do is to plot one graph that shows the scatterplot for the three groups (each group represented

Dear R-helpers, I have found a slightly annoying problem when trying to plot lines on graphs. I first created my data using tapply, thus:- y1=as.vector(fit1$coef$random$id) x1=tapply(o1,id,median,na.rm=T) x2=tapply(o2,id,median,na.rm=T) #then I plot the data, thus:- plot(x1[x2==0],y[x2==0]) #if I now try to fit the linear regression, R 'hangs up'

Dear r-helpers, Spencer Graves and Manual Morales proposed the following methods to simulate p-values in lme4: ************preliminary************ require(lme4) require(MASS) summary(glm(y ~ lbase*trt + lage + V4, family = poisson, data = epil), cor = FALSE) epil2 <- epil[epil$period == 1, ] epil2["period"] <- rep(0, 59); epil2["y"] <- epil2["base"]

Dear R Helpers, I have noticed that when I use lmer to analyse data, the summary function gives different values for the AIC, BIC and log-likelihood compared with the anova function. Here is a sample program #make some data set.seed(1); datx=data.frame(array(runif(720),c(240,3),dimnames=list(NULL,c('x1','x2','y' )))) id=rep(1:120,2); datx=cbind(id,datx) #give x1 a

Dear R developers, I noticed a bug in the stats4 package, specifically in the confint method applied to ?mle? objects. In particular, when some ?fixed? parameters define the log likelihood, these parameters are stored within the mle object but they are not used by the ?confint" method, which retrieves their value from the global environment (whenever they still exist). Sample code: >

Hello dear R help members. I am trying to understand the anova.rq, and I am finding something which I can not explain (is it a bug?!): The example is for when we have 3 nested models. I run the anova once on the two models, and again on the three models. I expect that the p.value for the comparison of model 1 and model 2 would remain the same, whether or not I add a third model to be compared

I am trying to find methods for testing and visualizing calibration to Cox models with time-depended coefficients. I have read this nice article <http://journals.sagepub.com/doi/10.1177/0962280213497434>. In this paper, we can fit three models: fit0 <- coxph(Surv(futime, status) ~ x1 + x2 + x3, data = data0) p <- log(predict(fit0, newdata = data1, type = "expected")) lp

Hi , I want to apply the following code fo my data with 400 predictors. I was wondering if there ia an alternative way instead of typing 400 predictors for the following code. I really appreciate your help. fit0<-lm(Y~1, data= mydata) fit.final<- lm(Y~X1+X2+X3+.....+X400, data=mydata) ??? step(fit0, scope=list(lower=fit0, upper=fit.final), data=mydata, direction="forward")

Colleagues, I have written an R function (see fully annotated code below), with which I want to process a dataframe within levels of the variable StepType. My program works, it processes the data within levels of StepType, but the usual headers that separate the output by levels of StepType are at the end of the listing rather than being used as separators, i.e. I get Regression results StepType