similar to: is there material about Longitudinal Data Analysis with R?

Greetings: I am trying to find a package/solution for panel (longitudinal) data analysis. Unfortunately it seems I don't know where to start. Could somebody offer a hint? Thanks, Mihai Nica Jackson State University 155 B Parkhurst Dr. Jackson, MS 39202 "No good deed will ever remain unpunished" [[alternative HTML version deleted]]

Hi Ruser I'm trying to replicate some SAS code. I have to add a spline to my longitudinal spaghetti plot. I have the plot, but I can't add the spline, a overall trend line. In the SAS code they use the command 'I=SM50S' and I would prefer something similar. I?m using R 2.10.1 on windows XP? I have made this working example. tolerance.pp <-

Hi, Now i am dealing with longitudinal data set and I want to see the rough marginal plot for 2 variables separately. I found the code from one example here, reading <- read.table("http://www.ats.ucla.edu/stat/R/examples/alda/data/reading_pp.txt", header=T, sep=",") reading[reading$id %in% c(4, 27, 31, 33, 41, 49, 69, 77, 87), ] xyplot(piat~age | id ,

I have been working through the book "Applied longitudinal data analysis: modeling change and event occurrence" by Judith D. Singer and John B. Willett. I have been working examples using SAS and also using it as an opportunity for learning to use R for statistical analysis. I ran into some difficulties in chapter 8 which deals with using structural equation modeling. I have tried to

Hi all, I was trying to fit a Gamma hierarchical model using "glmer", but got weird error message that I could not understand. On the other hand, a similar call to the glmmPQL leads to results that are close to what I expect. I also tried to change tha "nAGQ" argument in "glmer", but it did not solve the problem. The model I was fitting has a simple structure - one

Hi all, I a semi-beginner with R and I am working with the plm package to examine a longitudinal dataset. Each individual in this dataset has a longitudinal weight for the probability that he or she remains in the sample. Unfortunately, I have not found an argument to use weights in the plm function? I tried ?weights=? like in standard lm or in nlme or lm4 but it does not work. I asked the

Dear List,   I have some longitudinal data, each patient was followed at times 0, 12, 16, 24 weeks and measure severity of a illness (0-worse, 1-same, 2-better). So, longitudinal response is categorical.  I was wondering whether lmer in R can fit a model for this type of data. If so, how we code? Or any other function in R that can fit this type of longitudinal data? Any suggestion would be

Dear R-help list members I gathered longitudinal data on fish behaviour which I try to analyse using a multi level model for change. Mostly, I am following Singer & Willett (2003), who provide also the S/R code for their examples in the book (e.g. http://www.ats.ucla.edu/stat/Splus/examples/alda/ch4.htm). Of course I am interested in change over time, but I am also very much interested in

it takes a long time to load the lme4 package.anyone else encounter this problem? > system.time(library(lme4)) 佋佖伻侂佇佽佉仾伒伳伋佁伡伃伆侟仯伜Matrix 佋佖伻侂佇佽佉仾伒伳伋佁伡伃伆侟仯伜lattice [1] 19.90 0.30 25.56 NA NA > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status Patched major 2 minor

Hi again! Following up my previous posting below (to which no response as yet), I have located a report which situates this type of question in a longitudinal modelling context. http://www4.stat.ncsu.edu/~dzhang2/paper/glm.ps Generalized Linear Models with Longitudinal Covariates Daowen Zhang & Xihong Lin (This work seems to originally date from around 1999). They consider an outcome Y,

hi, i am using the RODBC package to read excel files using odbcConnectExcel and susequently sqlFetch to read the contents of the file. the file that i use is just a matrix of numbers thats all. no headers and column names. what happens is that the sqlFetch is not reading my first row of numbers. i have tried different combinations of colnames and rownames logical values but that first row is not

i want to study R programming by studying the existing code from R itself,but i don't know how to read the code,can any one give me some guide? my R is installed in /usr/lib/R/ [ronggui at mylinux ronggui]$ /usr/lib/R/ afm bin doc etc include library modules share > version _ platform i586-mandrake-linux-gnu arch i586 os linux-gnu system i586,

here is my system memory: ronggui at 0[ronggui]$ free total used free shared buffers cached Mem: 256728 79440 177288 0 2296 36136 -/+ buffers/cache: 41008 215720 Swap: 481908 60524 421384 and i want to cluster my data using hclust.my data has 3 variables and 10000 cases.but it fails and saying have not

entercount an error with demo(scoping). > demo(scoping) demo(scoping) ---- ~~~~~~~ ___snip_____ > ross$balance() Your balance is 120 > try(ross$withdraw(500)) Error in ross$withdraw(500) : You don't have that much money! > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status beta major 2 minor

Dear R-help subscribers, I use xyplot to plot longitudinal data as follows: score<-runif(100,-4,5) group<-sample(1:4,100,rep=T) subject<-rep(1:25,4) age<-rep(runif(4,1,40),25) df<-data.frame(score,group,age,subject) xyplot(score~age|group, group=subject, panel=function(...){ panel.loess(...,lwd=4) panel.superpose(...)} ,data=df) this produced a plot with four panels one for each

Hi all: I have a question about the sample size calculation. It's a pilot study,which includes 2 groups(low,high),3 time point(3,6,9 monthes).Each person has 3 results which according to the 3 time points.So it's a longitudinal study. I want to calculate the minimum sample size from the pilot study, but can't find the solution since the data is highly skewed and it's a

Hi all, I asked this before the holiday, didn't get any response. So would like to resend the message, hope to get any fresh attention. Since this is not purely lme technical question, so I also cc-ed R general mailing list, hope to get some suggestions from there as well. I asked some questions on how to analyze longitudinal study with only 2 time points (baseline and a follow-up)

Hi all, can the glm package be used to estimate a logit model to panel data? I am asking this because stata has a standard logit model and then an xtlogit for longitudinal data. Is there something similar in R? Thank you jcm [[alternative HTML version deleted]]

Dear R-Users! Is there a possibility in R to do analyze longitudinal survey data (repeated measures in a survey)? I know that for longitudinal data I can use lme() to incorporate the correlation structure within individual and I know that there is the package survey for analyzing survey data. How can I combine both? I am trying to calculate design-based estimates. However, if I use svyglm() from

The incorrect result incurs when the file path contains Chinese character. It seems that dirname/basename action on unit of byte instead of char, so the result in the following example is half of what is expected. > g<-"d:\\$BG!2L4^M-CfJ8(B\\$BG!2L4^M-CfJ8(B.txt" > dirname(g) [1] "d:/$BG!2L4^(B" > basename(g) [1] "$BG!2L4^M-(B" -- HUANG Ronggui,