similar to: predictions in nlme without fixed covariantes

Full_Name: Renaud Lancelot Version: Version 2.3.0 (2006-04-24) OS: MS Windows XP Pro SP2 Submission from: (NULL) (82.239.219.108) I think there is a bug in predict.lme, when a polynomial generated by poly() is used as an explanatory variable, and a new data.frame is used for predictions. I guess this is related to * not * using, for predictions, the coefs used in constructing the orthogonal

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

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

Dear R- Community, to learn i reanalysed some data provided and analysed by Zuur et. al. in their book "Mixed effect models and Extensions in Ecology with R". When i run the last command i get a warning message i dont understand. Loyn<- read.table(file = "loyn.txt",header = TRUE) Loyn$L.AREA<- log10(Loyn$AREA) fGRAZE <-factor(Loyn$GRAZE) M0<- lm(ABUND~ L.AREA

Dear R-help, I can't plot nls objects for some reason. The following example, taken from help(plot.nls) illustrates the problem: > data(Orthodont) > fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject) > plot(fm1, resid(., type = "p") ~ fitted(.) | Sex, abline = 0) Error in do.call(plotFun, as.list(args)) : couldn't find function

Dear all, I'm not sure whether this is intended behaviour or a bug. The path returns from normalizePath is different when the directory doesn't exist. I have included a reproducible example. path <- tempfile() missing.dir <- normalizePath(path, winslash = "/", mustWork = FALSE) dir.create(path) existing.dir <- normalizePath(path, winslash = "/", mustWork =

Dear all, Sweave chokes when using "\\" in the path to the Rnw file. Using "/" works fine. The problem is that Eclipse+StatET uses "\\" in the filename. And example of the error, traceback and sessionInfo are given below. Best regards, Thierry > Sweave("Q:\\BMK\\cursussen\\interne_opleiding\\deelnemerslijst.Rnw", syntax="SweaveSyntaxNoweb")

Dear all, I'm trying to connect to an MSAccess database (ArcGIS personal geodatabase). I keep getting an error about the channel when using sqlQuery(). However, sqlTables() does not complain about the channel and lists all tables in the database. If I try sqlFetch(), then R crashes. I'm happy to hear suggestions on how to solve this. Best regards, Thierry > MDB <-

Hello, We use drc to fit dose-response curves, recently we discovered that there are quite different standard error values returned for the same dataset depending on the drc-version / R-version that was used (not clear which factor is important) On R 2.9.0 using drc_1.6-3 we get an IC50 of 1.27447 and a standard error on the IC50 of 0.43540 Whereas on R 2.7.0 using drc_1.4-2 the IC50 is

Dear all, We have a problem with reading some characters correctly from an UTF-16 encoded database. The code below givens the correct characters on Ubuntu with the_driver = {ODBC Driver 13 for SQL Server}. On Windows (with the_driver = {SQL Server}), special characters like '?' and '?' are returned as '?'. I've added the sessionInfo() output from both machines. Any

Dear all, install.packages("lme4") fails with error Error in read.dcf(file = tmpf) : cannot open the connection In addition: Warning message: In read.dcf(file = tmpf) : cannot open compressed file '//servername/repository_path/bin/windows/contrib/3.2/PACKAGES', probable reason 'No such file or directory' the repositories set in .Rprofile are

Dear all, A colleague of mine reported a problem that I fail to understand completely. He has a number of .csv files that look all very straightforward, and they all read in perfectly well using read.csv() on both his and my computer. When we try the exact same R version on the university server however, suddenly all numeric variables turn into factors. The problem is resolved by deleting the

Dear all, My package has Depends: lme4.0 in the DESCRIPTION. I need to extract the fixed effect of a model and their standard errors. I use coef(summary(model)) inside a function to do that. Model is the output of a call to glmer() from the lme4.0 package. coef(summary(model)) throws an error: $ operator is invalid for atomic vectors I have tracked it down to a problem with summary(model)

I have two questions related to plotting predicted values for a linear mixed model using xyplot: 1: With a groups= argument, I can't seem to get the key to appear inside the xyplot. (I have the Lattice book, but don't find an example that actually does this.) 2: With lme(), how can I generate confidence bands or prediction intervals around the fitted values? Once I get them, I'd

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

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 =

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

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

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 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 <-