R Development Page
Contributed R Packages
Below is a list of all packages provided by project lme4  Mixedeffects models.
Important note for package
binaries: RForge provides these binaries only for
the most recent version of R, but not for older
versions. In order to successfully install the
packages provided on RForge, you have to switch
to the most recent version of R or, alternatively,
install from the package sources (.tar.gz).
Gqr  Determine knots and weights for Gaussian quadrature rules


Determine the knots and the weights for Gaussian quadrature
rules based on Legendre, Chebyshev, Gegenbauer, Jacobi, Laguerre,
Hermite, Exponential or Rational kernels. Generalized forms of the
kernels can be used. 

Version: 0.20 
Last change: 20121020 22:43:40+02 
Rev.: 1791 

Download:
(.tar.gz) 
(.zip) 
Build status: Current 

R install command:
install.packages("Gqr", repos="http://RForge.Rproject.org") 


MEMSS  Data sets from Mixedeffects Models in S


Data sets and sample analyses from Pinheiro and Bates,
"Mixedeffects Models in S and SPLUS" (Springer, 2000). 

Version: 0.92 
Last change: 20140311 16:28:59+01 
Rev.: 1887 

Download:
(.tar.gz) 
(.zip) 
Build status: Current  Stable Release: Get MEMSS 0.92 from CRAN 

R install command:
install.packages("MEMSS", repos="http://RForge.Rproject.org") 


SASmixed  Data sets from "SAS System for Mixed Models"


Data sets and sample lmer analyses corresponding
to the examples in Littell, Milliken, Stroup and Wolfinger
(1996), "SAS System for Mixed Models", SAS Institute. 

Version: 1.04 
Last change: 20140311 15:07:15+01 
Rev.: 1886 

Download:
(.tar.gz) 
(.zip) 
Build status: Current  Stable Release: Get SASmixed 1.04 from CRAN 

R install command:
install.packages("SASmixed", repos="http://RForge.Rproject.org") 


lme4  Linear mixedeffects models using Eigen and S4


Fit linear and generalized linear mixedeffects models.
The models and their components are represented using S4 classes and
methods. The core computational algorithms are implemented using the
Eigen C++ library for numerical linear algebra and RcppEigen "glue". 

Version: 0.999999111 
Last change: 20130115 16:46:16+01 
Rev.: 1794 

Download:
(.tar.gz) 
(.zip) 
Build status: Current  Stable Release: Get lme4 1.110 from CRAN 

R install command:
install.packages("lme4", repos="http://RForge.Rproject.org") 


lme4.0  Linear mixedeffects models using S4 classes


Fit linear and generalized linear mixedeffects models.
This is the implementation of lme4 available on CRAN and developed up to 2011.
It has been renamed to lme4.0, and is now deprecated in favor of the new
lme4 package, for everything new.
For reproducibility of past research and data analysis, lme4.0 is kept
available. For the time being, code and other packages who have made
extensive use of the inner structure, e.g., of lmer() results, will have
to depend on lme4.0 until their code can be adapted. 

Version: 0.9999994 
Last change: 20140705 18:27:42+02 
Rev.: 1890 

Download:
(.tar.gz) 
(.zip) 
Build status: Current 

R install command:
install.packages("lme4.0", repos="http://RForge.Rproject.org") 


lme4a  Linear mixedeffects models using S4 classes


Fit linear and generalized linear mixedeffects models. 

Version: 0.99968751 
Last change: 20120112 16:08:53+01 
Rev.: 1505 

Download:
(.tar.gz) 
(.zip) 
Build status: Current 

R install command:
install.packages("lme4a", repos="http://RForge.Rproject.org") 


lme4b  Linear mixedeffects models using S4 classes


Fit linear and generalized linear mixedeffects models. 

Version: 0.99937560 
Last change: 20100804 16:29:59+02 
Rev.: 1040 

Download:
(.tar.gz) 
(.zip) 
Build status: Current 

R install command:
install.packages("lme4b", repos="http://RForge.Rproject.org") 


mlmRev  Examples from Multilevel Modelling Software Review


Data and examples from a multilevel modelling software review
as well as other wellknown data sets from the multilevel modelling
literature. 

Version: 1.06 
Last change: 20140311 15:06:21+01 
Rev.: 1885 

Download:
(.tar.gz) 
(.zip) 
Build status: Current  Stable Release: Get mlmRev 1.06 from CRAN 

R install command:
install.packages("mlmRev", repos="http://RForge.Rproject.org") 


Build status codes
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