similar to: plot.design()

I've moved nlme from Depends to Imports in my coxme package. However, a few of the examples for lmekin use one of the data sets from nlme. This is on purpose, to show how the results are the same and how they differ. If I use data(nlme::ergoStool) the data is not found, data(nlme:::ergoStool) does no better. If I add importFrom(nlme, "ergoStool") the error message is that

Dear ListeRs, I am trying to fit a heteroscedastic multilevel model using lmer{lme4- package). Take, for instance, the (fictive) model below. lmer(test.result ~ homework + Sex -1 + (1 | School)) Suppose that I suspect the error terms in the predicted values to differ between men and women (so, on the first level). In order to model this, I want the 'Sex'-variable to be random on

Hi all, I have a questions regarding mixed effects models: I'm trying to plot e.g. fitted vs residuals for each level of the random effects, and i'm getting the same error. I guess this might be a problem of the graphic capabilities of R. Is there any way to obtain those plots? library(nlme) attach(ergoStool) names(ergoStool) [1] "effort" "Type"

Dear R users, I would like to exactly reproduce a figure like the 1.5 or 1.9 or 4.13 from the book Mixed effects models in S and S-Plus. Not for the sake of it, but because I have my own data I would like to plot in that fashion (no colors) If I write plot(ergoStool) I can get a good informative plot with colors, but I would like to have a B&W one instead. I've played a little with

Using the "ergoStool" data cited in Mixed-Effects Models in S and S-PLUS by Pinheiro and Bates as an example, we have ======== > library(nlme) > fm <- lme(effort~Type-1, data=ergoStool, random=~1|Subject) > summary(fm) Linear mixed-effects model fit by REML Data: ergoStool AIC BIC logLik 133.1308 141.9252 -60.5654 Random effects: Formula: ~1 | Subject

Hello, I've had no luck finding an R package that has the ability to estimate a Tobit model allowing for heteroskedasticity (multiplicative, for example). Am I missing something in survReg? Is there another package that I'm unaware of? Is there an add-on package that will test for heteroskedasticity? Thanks for your help. Cheers, Alan Spearot -- Alan Spearot Department of Economics

Dear list, i am a student of psychology and have to do a multilevelanalysis on some data. About that i have one general and one specific question. This is what i have copied from the help-file on lme: data(bdf) fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf, random = ~ IQ.ver.cen | schoolNR) summary(fm) after summary(fm) i get the following error:

Hi, does anyone out there have a recommendation for multilevel / random effects and longitudinal analysis? My dream book would be something that's both accessible to a non-statistician but rigorous (because I seem to be slowly turning into a statistician) and ideally would use R. Peter

Greetings- A relatively small request, but here goes. I have some crosstabs, generated with table(), in R: > table(pg.df$grouptype,pg.df$age) 0 1 2 3 4 B 1 3 6 8 3 C 1 3 4 10 7 P 0 2 9 9 8 S 2 9 4 5 16 U 0 15 15 3 0 X 0 0 0 0 0 I would like to export these in latex format using xtable(). But it appears there's no appropriate method for

Greetings- I'm venturing into a new (for me) area of using R: some presentation graphics based on R data. I'd like to compare two distributions of ordinal variables in relatively small (N=203 and 207) subsets of an R dataset. I can get a reasonably good picture of the distributions' differences with: x11() plot(table(hcd.df$auth.sum[hcd.df$datecat==1]),

Greetings- Running R 2.4.0 under Debian Linux, I am getting a memory error trying to read a very large file: > library(foreign) > oldgrades.df <- read.spss('Individual grades with AI (Nov 7 2006).sav',to.data.frame=TRUE) Error: cannot allocate vector of size 10826 Kb This file is, granted, quite large: aperrin at perrin:/data0/grading$ ls -l total 630304 -r-xr-xr-x 1 aperrin

Greetings- I have some data on which I need to do something like a Hierarchical Linear Model (please bear with me, I'm only learning the technique so I don't know yet if my language is correct). Essentially I'm analyzing data at two levels simultaneously; data are about individuals an organizations of which they are members. Can someone point me toward an appropriate package in R?

Greetings- I am in the process of constructing a nonlinear model using nlme. The model is attempting to fit a nested data structure from some public-opinion data (the data are from individuals nested within organizations). The question I have is fairly simple (I hope). The data were collected in two stages: a 15,000-subject randomly-sampled telephone interview (the SCREEN), with 2,517 subjects

Greetings. I'm planning to make a point in a meeting tomorrow and want to make sure I've got my ducks in a row. I've got four distinct vectors: years, fec, gss, and nes. Years is simply seq(1972,1996,by=4), and the other three are measures of voter participation in US elections in those years. fec is the Federal Election Commission's numbers, gss and nes are the General Social

Greetings. I've been experimenting with some algorithms for document classification (specifically, a Naive Bayes classifier and a kNN classifier) and I would now like to calculate some inter-rater reliability scores. I have the data in a PostgreSQL database, such that for each document, each measure (there are 9) has three variables: ap_(measure), nb_(measure), and knn_(measure). ap is me

In discussing permutation tests, _Modern Applied Statistics With S Plus_ suggests this (IMHO) rather elegant approach to generating a distribution of t-tests: d<- ...some data... ttest <- function(x) mean(x)/sqrt(var(x)/length(x)) n<-1000 res<-numeric(n) for(i in 1:n) res[i] <- ttest(x<-d*sign(runif(10)-0.5) The problem is that the sign(runif) results in random permutation of

I'd like to get summary statistics (really just a mean would be fine) for a vector in a data frame, but split based on the value of another vector. That is, I have a data frame (hcd.df) with variables datecat (which is always 1 or 2) and auth.sum (-8..+8). I've used xtabs to get chi-square comparisons, but what I need now is a simple mean of auth.sum where datecat is 1 and another where

Greetings. I'd like to generate a graph that displays two distributions as side-by-side bar graphs, then plots a smoothed line of the distribution on top. The idea is to be able to visually compare the distributions. I've done the following, but the axes don't line up. Any suggestions? barplot(table(hcd.df$datecat, hcd.df$auth.sum), beside=TRUE,

Greetings- I have a strange problem displaying a graph from R (1.3.1, linux) in a LaTeX document of documentclass seminar. I'm using graphicx to include the file: \usepackage{graphicx} ... \resizebox{\textwidth}{\textheight}{\includegraphics{crime.eps}} When I do this, the entire slide (including the page number) is rotated 180 degrees. Any ideas why this happens? The graph was created

Earlier today I posted a problem importing an R graph into a LaTeX file of seminar class: specifically, the graphic was showing up rotated 180 degrees, along with the rest of the page it was on. In a real victory for open-source software, I got lots of responses with three distinct approaches, each of which appears to solve the problem. Try getting fast, correct help from Microsoft on a Sunday