similar to: lmList with NAs

Dear List: I have a data set with over 7000 students with about 4 observations over time per student. I want to examine the within-group fits of a random sample of this group as it takes forever to compute and draw all 7000 regressions. Here is the code I have used so far. >group<-groupedData(math~year|childid, data=scores) >group.list<-lmList(group)

Dear list In HLM, one can specify a covariate at one of the "levels". For example, if the data structure are repeated observations nested within students nested within schools, school size might be a covariate that is used at level 3, but not at the other levels. In HLM this is rather easy to do. However, how can one specify a covariate in R for only one of the levels? I have a

Dear list: I am trying to merge two files together from output I get based on the coef() command. Here is what I am running into. I have two simple linear mixed models > mod1.lme<-lme(math~year, data=sample, random=~year|childid/schoolid) > mod2.lme<-lme(math~year, data=sample, random=~year|childid) I then call the coefficients and store them in the following objects using >

This question comes up periodically, probably enough to give it a proper thread and maybe point to this thread for reference (similar to the 'conservative anova' thread not too long ago). Moving from lme syntax, which is the function found in the nlme package, to lmer syntax (found in lme4) is not too difficult. It is probably useful to first explain what the differences are between the

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

Dear List: I am having difficulties with the fitted values at different levels of a multilevel model. My data set is a series of student test scores over time with a total of 7,280 observations, 1,720 students nested witin 60 schools. The data set is not balanced. The model was fit using eg.model.1<-lme(math~year, random=~year|schoolid/childid, data=single). When I call the random

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

Dear colleges, I would like to use the lmList function. I have installed the lme4 library but when I try to use the lmList function I get this error message. Error: could not find function "lmList" Here you can see what kind of messages I am getting when installing lme4 package. Does anyone know how to solve this problem? Thanks Rosario > install.packages() --- Please select a

Dear all, I have a question on handling of missing values in lmList. My data set have continuous predictor and response, x and y, and a grouping variable group.id. All these variables have NAs and the data set also has several other variables that also contains NAs. To create the lmList-object seems to work fine: y.list <- lmList(y ~ x | group.id, data=mydata, na.action=na.omit) However,

In R, we currently have the functions anovalist.lm and anova.glmlist S / S-plus has anova.lmlist anova.glmlist On the other hand, the [n]lme package (library) of Doug Bates and Jose Pinheiro has an "lmList" class and an anova.lmList(.) method for that. We are considering to use anovalist.lm and anovalist.glm instead of the S/S-plus names mentioned above. These functions

Hello, in R-2.1.0 I'm trying to prodice trellis plots from an lmList object as described in the help for plot.lmList. I can generate the plots from the help, but on my own data plotting fails with an error message that I cannot interpret (please see below). Any hints are greatly appreciapted. kind regards, Arne > dim(d) [1] 575 4 > d[1:3,] Level_of_Expression SSPos1 SSPos19

Dear community, I'm trying to examine my grouped data following page 6 http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-mixed-models.pdf. I'm trying lmList this way: model.list <- lmList(log(v.dep) ~ log(v2) +log(v4) + v3 | v5, subset = v6=0, data=data) and obtain this error message: In Ops.factor(v4, v4) : | not meaningful for factors My original model is

I'd like to fit a GLM to each of a number of subsets of some data. The `family' argument to `lmList' (in lme4) has given me cause for optimism, but so far I've only been able to achieve linear model fits. For example > df <- data.frame(gp = gp.temp <- factor(rep(1:3, each = 100)), x = x.temp <- rnorm(300), y = rpois(300, exp((-1:1)[gp.temp] + x.temp))) Then a call to

Dear all, I've got a problem in including square variables in lme and lmlist functions. I've tried to work on Oxboys data of Pinheiro and Bates'book, which consist of the heights of 26 boys, each mesured on nine different occasions : > Oxboys Grouped Data: height ~ age | Subject Subject age height Occasion 1 1 -1.0000 140.50 1 2 1 -0.7479 143.40

Full_Name: Vaidotas Zemlys Version: 2.9.0 OS: Ubuntu 8.10 Submission from: (NULL) (213.197.173.50) Steps to reproduce the bug: library(nlme) data(Oxboys) qm=lmList(height~age|Subject,data=Oxboys) grid=with(Oxboys,expand.grid(age=seq(min(age),max(age),length=50),Subject=levels(Subject))) res <- predict(qm,grid,se=TRUE) Erreur dans if (pool) { : l'argument est de longueur nulle res <-

Dear Martin, Have you try to create a new variable for age squared, say agesq? If you fit the model using this new variable you should get the coefficients. So your new model is something like height~age+agesq I hope this helps, Saghir > -----Original Message----- > From: MARTIN Ludovic [SMTP:martinl@mathinfo.ens.univ-reims.fr] > Sent: Wednesday, 07 May, 2003 2:02 PM > To:

Hello, I installed the newest version of R (3.0.2) as well as the newest version of nlme (3.1-113) in order to use summary.lmList and other nlme functions. Once loading the new library, lmList and summary.lm can be found, but a number of additional functions cannot be found via command. Versions installed and loaded are correct. Any suggestions on how to allow for these functions of the new

Greetings, I just found out a bug in the function lmList of the package nlme with R 2.8.1 running under windows XP 32-bits. I have a data table with various columns corresponding to continuous variables as well as treatment variables taken on several years and several sites. Here is an example : Id year treatment A treatment B variable1 variable2 variable3 1

Over on StackOverflow someone is trying to get this code to work: library("nlme") fm2Pixel.lis<-lmList(pixel~day+I(day^2)|Dog, Pixel) summary(fm2Pixel.lis) (results: Error in `[<-`(`*tmp*`, use, use, ii, value = lst[[ii]]) : subscript out of bounds) http://stackoverflow.com/questions/32680306/plotting-individual-confidence-intervals-for-the-coefficients-in-the-lmlist-fit

I am using lmList, which takes 'Data' partitioned according to the levels of a grouping factor (gf) and individual 'lm' fits are obtained for each 'data'partition, using a model defined as in "lm". So my call to lmList looks something like: > mg.lis <- lmList(strmbf ~ age1c + gender1 + sysbp.clinic + + diabp.clinic + ldl1 + mets.total + bmi1c |