similar to: lme funcion in R

Hi all! I am working on a nested lme model with one fixed effect ("treatment", which 3 levels) and two random effects for "Individuals" (four of them) within "treatment" and "replicate -2 levels-" within "individual" within "treatment". For doing so, I´ve been trying to create a factor for Individual%in%Treatment, say IT by

Hi everybody! I'm sure that I overlook something and feel quite stupid to ask, but I have not found an easy solution to the following problem: Take e.g. the Orthodont data from the nlme package: > head(Orthodont) Grouped Data: distance ~ age | Subject distance age Subject Sex 1 26.0 8 M01 Male 2 25.0 10 M01 Male 3 29.0 12 M01 Male 4 31.0 14 M01 Male

Hi, I'm new at this, I'm very confused, and I think I'm missing something important here. In our pet example we have this: > fm <- lme(Orthodont) > plot(Orthodont) > plot(augPred(fm, level = 0:1)) which gives us a trellis plot with the females above the males, starting with "F03", "F04", "F11", "F06", etc. I thought the point of

Hi, I am trying to run a panel regression where I have a matrix of observations and a matrix of independant variables - examples would trying to predict countries's GDP with their data on education, FDI, tax rates, over time. For the purpose of simplicity, my data would be: dep = matrix(rnorm(50),ncol=5) indep1 = matrix(rnorm(50),ncol=5) indep2 = matrix(rnorm(50),ncol=5) >From what I

Hi everyone, I have a quick and probably easy question about lme for this list. Say, for instance you want to model growth in pituitary distance as a function of age in the Orthodont dataset. fm1 = lme(distance ~ I(age-8), random = ~ 1 + I(age-8) | Subject, data = Orthodont) You notice that there is substantial variability in the intercepts (initial distance) for people at 8 years, and that

Hi All, I am trying to run rsync from HP11.00 machine (source) to HP11.11 machine, as test for migration plan. The data on the source is not changing since it is snapshot of active data. Every time we try to run the following command: timex rsync -avuz --delete isynh09:/snap We get the following error: receiving file list ... done mknod

Hi, I am having some difficulties with matrix operations. It is a little hard to explain it so please bear with me. I have a very large data set, large enough that it needs to be split in parts in order to deal with. I can work things on these "parts" but the problem lies in adding together these parts for the final answer. So that been said, let's say that i split the data in 2

Hi, R users, I'm wondering how I can aggregate data in R with different functions for different columns. For example: x<-rep(1:5,3) y<-cbind(x,a=1:15,b=21:35) y<-data.frame(y) I want to aggregate "a" and "b" in y by "x". With "a", I want to use function "mean"; with "b", I want to use function "sum". I tried:

Hi, R users, I'm using while() in R to set a condition. My condition is: i<523 or i>535. How should I write this in R? I try "while (i<523 or i>535)" and it does not work. Thanks. Garry On Tue, Nov 10, 2009 at 11:26 AM, Hongwei Dong <pdxdong@gmail.com> wrote: > Exactly! Thanks, Duncan. > > Let me re-phrase me question like this: > > 1) X_i values

Consider the following plot that shows separate regression lines ~ age for each subject in the Pothoff-Roy Orthodont data, with separate panels by Sex: library(nlme) #plot(Orthodont) xyplot(distance ~ age|Sex, data=Orthodont, type='r', groups=Subject, col=gray(.50), main="Individual linear regressions ~ age") I'd like to also show in each panel the pooled OLS

I have spent a whole afternoon searching for the solution, but got nothing so far. It should be a simple problem. I have two datasets to merge. The first one just contains two ID columns and it looks like: FromID ToID 1 2 1 3 2 1 2 3 3 1 3 2 The second one contains a ID column and a variable: ID X 1 100 2 150 3

R-helpers: I would like to measure the correlation coefficient between the repeated measures of a single variable that is measured over time and is unbalanced. As an example, consider the Orthodont dataset from package nlme, where the model is: fit <- lmer(distance ~ age + (1 | Subject), data=Orthodont) I would like to measure the correlation b/t the variable "distance" at

I work for a school dist, and I am having a bit of trouble with the "Student Server" We have about 3000 students all with their own accounts. I had the samba server setup to share their home directories but their home directories are the same as their login name. So jamie.mcparland would be an example of a share name. But in Win 9X it gets truncated to jamie.mcparla then we get the error

Hi all I’m in desperate need of help. I’m working with a grouped data object, called Orthodont in the nlme package in R, and am trying to fit various models (learning methods for my thesis), but one of the variables in the object is numeric, (age) and I need it to be a factor. I’ve tried: as.factor(Orthodont$age) as.factor(as.character(Orthodont$age)) and various other things, but when I then

Many thanks for your very useful comments and suggestions. Renaud 2006/5/30, Prof Brian Ripley <ripley at stats.ox.ac.uk>: > On Tue, 30 May 2006, Prof Brian Ripley wrote: > > > This is not really a bug. See > > > > http://developer.r-project.org/model-fitting-functions.txt > > > > for how this is handled in other packages. All model-fitting in R used =

Hi, R users, I'm wondering if I can identify an element in a column by an element in another column. For example: x<-1:10 y<-11:20 z<-cbind(x,y) z x y [1,] 1 11 [2,] 2 12 [3,] 3 13 [4,] 4 14 [5,] 5 15 [6,] 6 16 [7,] 7 17 [8,] 8 18 [9,] 9 19 [10,] 10 20 What I want to do is: when x=5, y=y-1 Anyone can tell me how to do this? Thanks. Gary [[alternative

Dear R-Users, Is it possible to get the covariance matrix from an lme model that did not converge ? I am doing a simulation which entails fitting linear mixed models, using a "for loop". Within each loop, i generate a new data set and analyze it using a mixed model. The loop stops When the "lme function" does not converge for a simulated dataset. I want to

In a paper I'm writing using Sweave, I make use of lattice graphics, but don't want to explicitly show (or explain) in the article text the print() wrapper I need in code chunks for the graphs to appear. I can solve this by including each chunk twice, with different options, as in <<ortho-xyplot1-code, keep.source=TRUE, eval=FALSE>>= library(nlme) library(lattice)

Hi, R users, Can anyone tell me how I can change the size of points in my plot? For example: x <- c(1,3,6,9,12) y <- c(1.5,2,7,8,15) plot(x,y,pch=20) How do I reduce the size of those points? Thanks. Gary [[alternative HTML version deleted]]

Dear R-help I'm working on a large dataset which I have divided into 20 subsets based on similar features. Each subset consists of observations from different locations and I wish to use the location as a random effect. For each group I want to select regressors by a stepwise procedure and include a random effect on the intercept. I use stepAIC() and lme(). (The lmer()-function doesn't