jamiefolson/lme4

Mixed-effects models in R using S4 classes and methods with RcppEigen

lme4: Mixed-effects models in R.

Recent/release notes

• The major user-visible change in release 1.1-7 is that most of the recent rash of false convergence warnings have been cleared up. As far as we know, any convergence warnings you get with lme4 >= 1.1-7 are actually cause for concern and should be handled in the usual ways (e.g. try alternative optimizers within lme4 or alternative R packages/software to cross-check the results; explore data for outliers or complete separation; center and scale continuous predictors).
• Otherwise, see the NEWS file (or news(Version=="1.1.7",package="lme4")).

Features

• Efficient for large data sets, using algorithms from the Eigen linear algebra package via the RcppEigen interface layer.
• Allows arbitrarily many nested and crossed random effects.
• Fits generalized linear mixed models (GLMMs) and nonlinear mixed models (NLMMs) via Laplace approximation or adaptive Gauss-Hermite quadrature; GLMMs allow user-defined families and link functions.
• Incorporates likelihood profiling and parametric bootstrapping.

Installation

On current R (>= 3.0.0)

• From CRAN (stable release 1.0.+)
• Development version from Github:

library("devtools"); install_github("lme4/lme4",dependencies=TRUE)

(This requires devtools >= 1.6.1, and installs the "master" (development) branch.) This approach builds the package from source, i.e. make and compilers must be installed on your system -- see the R FAQ for your operating system; you may also need to install dependencies manually. Specify build_vignettes=FALSE if you have trouble because your system is missing some of the LaTeX/texi2dvi tools.

• Usually up-to-date development binaries from lme4 r-forge repository:

install.packages("lme4",
   repos=c("http://lme4.r-forge.r-project.org/repos",
          getOption("repos")[["CRAN"]]))

(these source and binary versions are updated manually, so may be out of date; if you believe they are, please contact the maintainers).

On old R (pre-3.0.0)

It is possible to install (but not easily to check) lme4 at least as recently as 1.1-7.

• make sure you have exactly these package versions: Rcpp 0.10.5, RcppEigen 3.2.0.2
• for installation, use --no-inst; this is necessary in order to prevent R from getting hung up by the knitr-based vignettes
• running R CMD check is difficult, but possible if you hand-copy the contents of the inst directory into the installed package directory ...

Of lme4.0

• lme4.0 is a maintained version of lme4 back compatible to CRAN versions of lme4 0.99xy, mainly for the purpose of reproducible research and data analysis which was done with 0.99xy versions of lme4.
• there have been some reports of problems with lme4.0 on R version 3.1; if someone has a specific reproducible example they'd like to donate, please contact the maintainers.
• Notably, lme4.0 features getME(<mod>, "..") which is compatible (as much as sensibly possible) with the current lme4's version of getME().
• You can use the convert_old_lme4() function to take a fitted object created with lme4 <1.0 and convert it for use with lme4.0.
• It currently resides on R-forge, and you should be able to install it with

install.packages("lme4.0", 
                 repos=c("http://lme4.r-forge.r-project.org/repos",
                         getOption("repos")[["CRAN"]]))

(if the binary versions are out of date or unavailable for your system, please contact the maintainers).