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...replacing pdLogChol I cannot reproduce with lmer. The obvious choice for me would be my model lmer2, but this is yielding different result. Somebody any idea? Thanks, Joris I am using R version 2.1.0 for Linux and the most recent downloads of Matrix and nlme #dataset from McLean, Sanders and Stroup F <- factor(c(1,1,1,1,1,1,2,2,2,2,2,2)) R <- factor(c(1,1,2,2,3,3,1,1,2,2,3,3)) s <- c(51.43,51.28,50.93,50.75,50.47,50.83,51.91,52.43,52.26,52.33,51.58,51.23) DS <- data.frame(F,R,s) DS$F <- as.factor(DS$F) DS$R <- as.factor(DS$R) library(nlme) lme1 <- lme(data = DS,s ~ F,ra...

...a time series originating from the routine collection of public health data. The package addresses epidemiologists and statisticians working with routine surveillance, but it also offers an infrastructure for developers of new detection algorithms. Implemented outbreak detection algorithms are: * Stroup et al. (1989) * Farrington et al. (1996) * A Bayesian predictive posterior approach * Time varying Poisson means as documented in Rogerson and Yamada (2004) * Approximate CUSUM method for time varying Poisson means by Rossi et al. (1999) * A generalized likelihood ratio detector for time varying...

...a time series originating from the routine collection of public health data. The package addresses epidemiologists and statisticians working with routine surveillance, but it also offers an infrastructure for developers of new detection algorithms. Implemented outbreak detection algorithms are: * Stroup et al. (1989) * Farrington et al. (1996) * A Bayesian predictive posterior approach * Time varying Poisson means as documented in Rogerson and Yamada (2004) * Approximate CUSUM method for time varying Poisson means by Rossi et al. (1999) * A generalized likelihood ratio detector for time varying...

...tricted maximum likelihood (REML) estimates for linear mixed-effects models with single or multiple nested levels of random effects. The library includes a SAS_Mixed directory with R transcripts of analyses paralleling those in the book "SAS System for Mixed Models" by Littell, Milliken, Stroup and Wolfinger. Please ensure that you get the lme_2.9-2.tar.gz file. The lme_2.9-1.tar.gz file has problems with installation of the help files and has the wrong version listed in the DESCRIPTION file. (If you really want to install lme_2.9-1.tar.gz you can do so by removing the file lme/man/[.p...

Dear R-users Coming from a proc mixed (SAS) background I am trying to get into the use of (n)lme. In this connection, I have some (presumably stupid) questions which I am sure someone out there can answer: 1) With proc mixed it is easy to get a hold on the estimated variance parameters as they can be put out into a SAS data set. How do I do the same with lme-objects? For example, I can see the

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