similar to: examine grouped data lmList

Dear R list members, I've turned up a strange discrepancy between results obtained from the lme function in the nlme package in R and results obtained with lme in S-PLUS. I'm using version 3.1-24 of nlme in R 1.4.1 under Windows 2000, and both S-PLUS 2000 and 6.0, again under Windows 2000. I've noticed discrepancies in a couple of instances. Here's one, using data from Bryk

Dear r-devel list members, Dirk Eddelbuettel brought the following problem to my attention. The code is abstracted from the appendix on mixed models from my R and S-PLUS Companion: > set.seed(12345) # for reproducibility > library(nlme) Loading required package: lattice > data(MathAchieve) > data(MathAchSchool) > attach(MathAchieve) > mses <- tapply(SES, School,

Hello R-Helpers, I was trying to use the lmList function to get the lmList graphic similar to Pinheiro and Bates (pg 33). I did not have a problem creating the graphic when I used the Orthodont data frame or 2 other data sets when there are no missing values. My data has missing values. Do I need to remove the missing values before the lmList function will work? for a small example: > a

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

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 |

Dear useRs, I am working on a series of field experiments (159 in total) carried out in different years in several locations. The cultivars in each experiment are not always the same, in fact they change over time. I would like to get the fitted values and MSE of the individual fits from the following lmList object, so I can use them to fit a mixed model using the fitted values and weight each

Hi all, Forgive me if this is an obvious one.... I want to make a plot of confidence intervals from an lmList object with a collection of simple linear models (lm(y~x)) using: plot(intervals(mylmList)) and sort the plot by increasing mean values for the intercept. Is there an easy way of doing this? I've tried the "order()" and "sort.list()" functions, but I suspect

Hi R-helpers. #I start with the reproducible example: firm<-c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10)) year<-c(rep(1998:2007,5)) industry<-c(rep(1,20),rep(5,10),rep(7,10),rep(9,10)) X1<-rnorm(50) X2<-rnorm(50,mean=0.5,sd=0.1) Y<-rnorm(50,mean=0,sd=0.5) data<-data.frame(firm, industry,year,X1,X2,Y) data #I need to calculate for all the industries the following

I'm having trouble understanding how functions in the subset argument for lmList search for the objects they need. This trivial example produces "Error in rownames(fakedf) : Object "fakedf" not found": library(nlme) fitbyID <- function() { fakedf <- data.frame(ID = gl(5, 10, 50), A = sample(1:100, 50), B = rnorm(50))

Dear R-devel members, I think I've found a minor bug in plot.intervals.lmList. ( The guide https://www.r-project.org/bugs.html suggests to report it here, as I do not have a bugzilla account.) Here is a minimal reproducible example to demonstrate the problem: fm1 <- lmList(distance ~ age | Subject, Orthodont) plot(intervals(fm1),ylab="a") This results in: "Error in