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Jos?? C. Pinheiro Training in UK - Analyzing Mixed-Effects Models with S-PLUS Mixed-effects models provide a powerful tool for analyzing grouped data. This course will overview the application of linear and nonlinear mixed-effects models in the analysis of grouped data, using the NLME software in S-PLUS to illustrate the different stages of model fitting. A new element to the course will cover

All, Sorry for overly simplistic question, but I can't seem to remember how to create the basic plot shown in Figure 1.1 of Pinheiro & Bates (2004; p.4). The y-axis delineates a factor (Rail) while the x-axis displays the distribution of a continuous variable (time) according to each level of the factor. Didn't see it in archives but perhaps I'm not searching on correct key words,

Hello! could you give me some advice where i can finde out/recieve/download a GLME package, written by Jose Pinheiro. i couldn'ti find it in the package lists (probably becouse it is still in a beta version). thank you for your replay

Dear Mixed Effect Friends, Somehow, R(1021, Windows) seem to run differently from S Plus: The soybean example from Pinheiro/Bates on page 290 fails in R. (Soybean1 is Soybean with the NA and "critical" case removed. Same procedure with full Soybean). > fm1Soy.lis<-nlsList(weight~SSlogis(Time,Asym,xmid,scal),data=Soybean1) > fm1Soy.nlme<-nlme(fm1Soy.lis) Error: Singularity

Hi everyone. I am trying to add a formula to my data using the groupedData function. My experiment consists of randomized block design using fruits, vegetation and time as factors. The idea is to see if fruits, vegetation and time explain the abundance of mice. I am using tree density as a covariate. So I tried to fit the following structure to my data. >

Hello, I am interested in using nlme to model repeated measurements, but I don't seem to get good CIs. With the code below I tried to generate data sets according to the model given by equations (1.4) and (1.5) on pages 7 and 8 of Pinheiro and Bates 2000 (having chosen values for beta, sigma.b and sigma similar to those estimated in the text). For each data set I used lme() to fit a model,

Hi all, I'm trying to figure out the example about mixed models in the Pinheiro and Bates book (Mixed-Effects Models in S and S-Plus, 2000, pp. 135-137). One thing I don't understand is: When I run the command fm1Orth.lm <- lm( distance ~ age, Orthodont ) followed by fm2Orth.lm <- update( fm1Orth.lm, formula = distance ~ Sex*age ) and then do summary(fm2Orth.lm)

Dear all, This question may be too basic quesition for this list, but if someone has time to answer I will be happy. I have tried to find out, but haven't found a consice answer. As an example I use "Pinheiro, J. C. & Bates, D. M. 2000. Mixed-effects models in S and S-PLUS. Springer, New York." page 225, where rats are fed by 3 different diets over time, which body mass has

Dear list members, I'm interested in showing that within-group statistical dependence is negligible, so I can use ordinary linear models without including random effects. However, I can find no mention of testing a model with vs. without random effects in either Venable & Ripley (2002) or Pinheiro and Bates (2000). Our in-house statisticians are not familiar with this, either,

Anybody know where I can get the Pinheiro/Bates book? I can't find a bookstore w/ stock and the publisher says they don't know when they'll have it again. Thanks. -Frank

Hi, I have a problem with compiling the new revision, the file Sifsegv_gc makes a call to the file Sigsegv.cpp but returns as file already allocated: ... llvm [3]: Compiling for Debug + Asserts Sigsegv.cpp build (bytecode) llvm [3]: Compiling Sigsegv.ll to Sigsegv.bc for Debug + Asserts build ( bytecode) llvm [3]: Compiling Sigsegv.bc to Sigsegv.s for Debug + Asserts build llvm [3]: Compiling for

Dear R-help, I am trying to create groupedData objects using the nlme library. I'm missing something basic, I know: Here is the first example in ch.1 of Pinheiro & Bates (2000): library(nlme) x2=Rail$travel;x1=Rail$Rail;eg1=data.frame(x1,x2);eg1gd=Rail print(eg1gd) x11();print(plot(eg1gd)) femodel=lm(x2~x1-1,data=eg1gd) print(femodel$coefficients) Result: x12 x15 x11

I am using rw0641. In my continuing quest to understand repeated measures analysis, I again return to lme. I exported the Potthoff and Roy data Orthodont.dat from S-PLUS 4.5 to avoid capture errors and ran the examples in the R help. I imported the data.frame with data <- read.table("Orthodont.dat",header=T) attach(data) and created the objects Orthodont.fit1 <-

How does one implement a likelihood-ratio test, to test whether the variances of the random effects differ between two groups of subjects? Suppose your data consist of repeated measures on subjects belonging to two groups, say boys and girls, and you are fitting a linear mixed-effects model for the response as a function of time. The within-subject errors (residuals) have the same variance in

All, I'm trying to create an augPred plot in the nlme library, similar to the plot on p.43 of Pinheiro & Bates (Mixed Effects Models in S and S-Plus) for their Pixel data. My data structure is the same as the example but I still get the error msg below. > comp.adj.UKV <- groupedData(adj.UKV ~ Time | Patient_no/Lisinopril, data = comp.adj.UKV.frm, order.groups = F) >

Dear R users, I would like to exactly reproduce a figure like the 1.5 or 1.9 or 4.13 from the book Mixed effects models in S and S-Plus. Not for the sake of it, but because I have my own data I would like to plot in that fashion (no colors) If I write plot(ergoStool) I can get a good informative plot with colors, but I would like to have a B&W one instead. I've played a little with

Dear List, While trying to define a customised CITATION file for a package, following R-exts, I realised that if I use only one 'citEntry' I got both a text description and a BibTex entry for the package, as for the 'nlme' package: -------------------------- citation('nlme') To cite package 'nlme' in publications use: Jose Pinheiro, Douglas Bates, Saikat

Is there a procedure for suggesting changes to HELP files of the core R distribution? If yes, what is it? If it would be considered a friendly gesture, I could find the relevant *.Rd file and submit a suggested modification to it someplace. Alternatively, I could just send suggestions someplace if they would receive appropriate consideration. On many occasions, I think of

I am trying to understand the proper way to encode the nesting structure for data in the context of nlme, in the specific case of individuals nested within species for which each individual is unique. I have searched through Pinheiro & Bates and also past postings, but without success. Take the Wafer data set which has 2 levels: Wafer (8 values) and Site nested within Wafer (10 values for

Hi, I was trying to run the example of Indomethacin kinetics from the book: ## From Pinheiro/Bates, Mixed-Effects-Models in S and S-Plus, ## Springer, Second Printing 2001, Section 6.2 library(nlme) plot(Indometh) fm1Indom.nls <- nls(conc~SSbiexp(time,A1,lrc1,A2,lrc2), data=Indometh) summary(fm1Indom.nls) plot(fm1Indom.nls,Subject~resid(.),abline=0) ## .... the last plot command gives me the