similar to: Modelling Heteroscedastic Multilevel Models

Dear All, I'm trying to model heteroscedasticity using a multilevel model. To do so, I make use of the nlme package and the weigths-parameter. Let's say that I hypothesize that the exam score of students (normexam) is influenced by their score on a standardized LR test (standLRT). Students are of course nested in "schools". These variables are contained in the

Dear expeRts, I am trying to plot a lme-object {package nlme) in such a way, that on a selected level the x-axis represents the value on a selected predictor and the y-axis represents the predicted-outcome variable. The graphs would than consist of several lines that each represent one group. I can't find such a plotting function. I could write such a function myself, based on

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:

Dear helpers, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value

Deal all, new as I am to developing packages for R-Project, I apologize on beforehand for questions that are too obvious. I am trying to 'add' a PDF document containing some detailed information to a package. The way I understand the Rexts.pdf document, I should add my .PDF document to the /inst/doc/ folder, and links to the files should be build automatically. However, after

Dear helpers, I've come up with what is probably a simple problem, but I cannot find the solution. I have a data-set containing survey-data from several countries. What I want to do is to perform some regression analyses, for each country separately. The question is, how to do this nicely (thus without repeating the same syntax with another `subset' argument). I thought of the

Dear R users, I am trying to get data from the clipboard into R on MacOSX. I tried the following, but got an error message: read.delim("clipboard") Error in file(file, "r") : unable to open connection In addition: Warning message: unable to contact X11 display Obviously, I'm not running R using X11. I'm wondering, can I import data from the clipboard on MacosX?

LS, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value

Dear helpeRs, I'm working with the map-package and came upon a problem which I couldn't solve. I hope onee of you can. If not, this can be seen as a suggestion for new versions of the package. I'm trying to create a map of some European countries, filled with colors corresponding to some values. Let's say I have the following countries and I assign the following colors

Dear R users, experimenting with the lm function in R, I've encountered some behaviour I don't understand with my limited knowledge of regression. I made a data-'set' of three measurements (see syntax below). Using lm (linear model) to fit the regression-line, I expected to find an intercept of 2.0 and a slope of 0, but in fact the slope is slightly below zero. Amazed by

Paul: I may have found the issue (which is similar to your conclusion). I checked using egsingle in the mlmRev package as these individuals are strictly nested in this case: library(mlmRev) library(nlme) fm1 <- lme(math ~ year, random=~1|schoolid/childid, egsingle) fm2 <- lmer(math ~ year +(1|schoolid:childid) + (1|schoolid), egsingle) Checking the summary of both models, the output is

Hi, I'm running some data simulations using (mixed effects)* regression models that show difficulty to converge. Therefore, I seek a way of capturing warnings (of false convergence) inside a loop. Inside that loop, I modify data and estimate a model. I do so many times with slightly different modifications of the data. Next, I extract some of the model parameters and store these in a matrix.

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

Greetings- I'm working through Pinheiro and Bates' _Mixed Effects Models in S and S-Plus_ using R (1.3.1 for linux). On page 13 (okay, so I haven't got that far :)) is: plot.design( ergoStool) which returns on my system: > plot.design(ergoStool) Error: couldn't find function "plot.design" any ideas? Thanks.

Hi R users, I need to draw a map of select European countries with country names shown on the map. Does anyone know how to do this in R? Also, is it possible to draw a historical map of European countries using R? Thanks a lot for your help. Maomao [[alternative HTML version deleted]]

Hi, I'm trying to import categorical data from SPSS to R using the script: xxx <-spss.get("xxx.por", use.value.labels=TRUE) but unfortunately am getting an error message 'error reading portable-file dictionary'. I have successfully imported data in the past. What could be the problem with this data? Thanks Simo

Hello, I have tried to generate numbers randomly which follow normal, Student-t and skewed Student-t distributions. However, when I check those series for heteroscedastisity test (ARCH) results are showing that there is no heteroscedastisity. As we all know, returns (financial returns) usually have heteroscedastisity. My question is, is it possible somehow generate random numbers which have

Dear List: I was able to run the following in nlme successfully, but the same model and code (same dataset) failed to run in lme4 and gave me the error message below. Any thoughts? lme(math~year, data=egsingle, random=~year|schoolid/childid) Error in lme(formula = math ~ year, data = egsingle, random = structure(list( : Unable to invert singular factor of downdated X'X

Hello, All: I want to simulate future observations from fits to heteroscedastic data. A simple example is as follows: (DF3_2 <- data.frame(y=c(1:3, 10*(1:3)), gp=factor(rep(1:2, e=3)))) # I want to fit 4 models # and simulate future observations from all 4: fit11 <- lm(y~1, DF3_2) fit21 <- lm(y~gp, DF3_2) library(nlme) (fit12 <- lme(y~1, data=DF3_2,

Dear list members, I am facing a 3-level model, for which my research hypotheses suggest that the variance of both level-1 and level-2 residuals may be a function of a level-3 variable. To be a bit more clear: I am fitting a longitudinal model for a panel of companies grouped in industries. I suggest that some industry variables may create 'unexpected' shocks at especific points in