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_____ From: Vera, Graciela : Insurance Services (BISCO) Sent: 10 March 2006 14:47 To: 'r-help-request@stat.math.ethz.ch' Subject: RE: .First functin I have not used R for some time. Please accept my apologies if my question has an obvious answer. I am trying to use R. For convenience and due to IT restrictions libraries additional to MASS have been stored in a different directory

Hi everyone I have the following situation: In a longitudinal study, subjects fill out a questionnaire every year (repeated measurements over time). Also, the subjects are nested within departments. There is an intervention going on over time. The outcome variable is continuous. Now I'd like to analyse two things: 1. Is there a significant change over time? I think this is done by a

Hi, I am trying to learn time series, and I am attending a colleague's course on Econometrics. However, he uses e-views, and I use R. I am trying to reproduce his examples in R, but I am having problems specifying a AR(1) model. Would anyone help me with my code? Thanks in advance! Reproducible code follows: download.file("https://sites.google.com/a/proxima.adm.br/main/ex_32.csv

I am having difficulty understanding the syntax of the nlme() function for nonlinear mixed models. The data frame is called Marouane.chlorophyll. The model involves a dependent variable (Absorb) and an independent variable (Ch.surf), which are both numeric variables in the data frame. The data are hierarchically grouped as Espece, Plante nested within Espece, and Feuille nested within Plante

_____ From: Vera, Graciela : Insurance Services (BISCO) Sent: 10 March 2006 14:47 To: 'r-help-request@stat.math.ethz.ch' Subject: RE: .First functin I have not used R for some time. Please accept my apologies if my question has an obvious answer. I am trying to use R. For convenience and due to IT restrictions libraries additional to MASS have been stored in a different directory

Dear friends - We have 25 rats, 14 of these subjected to partial removal of kidney tissue, 11 to sham operation, and then followed for 6 weeks. So far we have data on 26 urine metabolites measured by NMR 7 times during the observation. I have smoothed the measurements by b.splines in fda including a roughness penalty, and inspecting the mean curves for nephrectomized and sham animals indicate

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

As of a moment ago (9 a.m., Monday, Jan. 8, 2001), the S Programming book by Venables and Ripley was once again selling for 17.98 American dollars at Amazon.com. Alas, I notice that "Mixed Effects Models in S and S-Plus" by Pinheiro and Bates now lists at Amazon for 97.25 American dollars, as opposed to about $70 a little while ago.

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

I am trying to calibrate a non linear mixed model with a AR(1) autocorrelation structure. This structure is indicated by the ACF plot. When calibrating the model without the AR(1), everything comes out nicely. However, when the AR(1) structure is included in the model, the Phi parameter estimate comes out to be 1. This result occurs with various starting values in the correlation statement. Am I

Hi, I'm trying to fit a model using variance components in R, but if very new on it, so I'm asking for your help. I have imported the SPSS database onto R, but I don't know how to convert the commands... the SPSS commands I'm trying to convert are: VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = MINQUE (1) /DESIGN

I added a bibliographic reference to one of my .Rnw documents, to wit: \begin{thebibliography}{9} \bibitem{Jose} Jos{\'{e}} C. Pinheiro and Douglas M. Bates, \emph{Mixed-Effects Models in S and S-PLUS}, Springer, 2000. \end{thebibliography} just before the \end{document}. When I run Sweave on the result these lines disappear without a trace. Is this intentional? Subquestion: is

Hello! I want to calculate the intra- and interrater reliability of my study. The design is very simple, 5 raters rated a diagnostic score 3 times for 19 patients. Are there methods/funtions in R? I only found packages to calculate interrater variability and intraclass correlation coefficients for matrices of n*m (n subjects, m raters) - I have n subjects, m raters and r repetitions. Can

Greetings- I have some data on which I need to do something like a Hierarchical Linear Model (please bear with me, I'm only learning the technique so I don't know yet if my language is correct). Essentially I'm analyzing data at two levels simultaneously; data are about individuals an organizations of which they are members. Can someone point me toward an appropriate package in R?

UNBIASED FACTS: ? Bugzilla & R-devel Mailing Lists: Remain unchanged: Understood as Ticketing platforms for bug pull requests on the R-devel Git Repository. ? Git Repository Options: A) Github (Cloud with Automated backups from GitHub to CRAN Server): https://github.com B) Gitlab (Selfhosted on CRAN): https://about.gitlab.com C) Phabricator (Selfhosted on CRAN): https://www.phacility.com D)

Hi, Out of curiosity, has anyone managed to use mail-trends[0] to analyse their e-mails. I thought about trying it out, but got stuck midstream. The mail-trends scripts work very well with gmail, but because they say it is supposed to work with _any_ IMAP server, I thought I could get it running with Dovecot too. I know this is NOT a mail-trends support group though, but I believe there is

Env: R 2.8.1, Win Xp, Eclipse/StatET In a .Rd file, I have an example containing the lines: # calculate Y M, using polynomial contrasts trends <- as.matrix(VocabGrowth) %*% poly(8:11, degree=3) colnames(trends)<- c("Linear", "Quad", "Cubic") [At the risk of a long message, I'll append the complete .Rd file at the end of this message, in case this was

Hi, does anyone out there have a recommendation for multilevel / random effects and longitudinal analysis? My dream book would be something that's both accessible to a non-statistician but rigorous (because I seem to be slowly turning into a statistician) and ideally would use R. Peter

In a lattice 11x11 with 6 repetitions, we want to compare lines to their two parents. 3 of the 6 repetitions are sprinkled and the 3 others not. There are 5 factors : hm (hydrous mode), variety, block, rep and grandrep. grandrep gathers two repetition, a sprinkled and a not (as in Split Plot !). I use lme but I have problems in random. Can someone help me ? Ibnou DIENG

Dear R users, I am currently analyzing a dataset using lme(). The model I use has the following structure: model<-lme(response~Covariate+TreatmentA+TreatmentB,random=~1|Block/Plot,method="ML") When I plot the residuals against the fitted values, I see a clear positive trend (meaning that the variance increases with the mean). I tried to solve this issue using weights=varPower(),