R package lsmeans: Least-squares means (predicted marginal means)

Features

For an overview, see the vignette -- also available via vignette("using-lsmeans", package = "lsmeans")
Least-squares means (a.k.a. predicted marginal means) are derived by using a model to make predictions over a regular grid of pridictor combinations (called a reference grid). These predictions may possibly be averaged (typically with equal weights) over one or more of the predictors. Such marginally-averaged predictions are useful for describing the results of fitting a model, particularly in presenting the effects of factors. The lsmeans package can easily produce these results, as well as various graphs of them (interaction-style plots and side-by-side intervals).
Estimation and testing of pairwise comparisons of LS means, and several other types of contrasts, are provided. There is also a cld method for display of grouping symbols.
Two-way support of the glht function in the multcomp package.
For models where continuous predictors interact with factors, the package's lstrends function works in terms of a reference grid of predicted slopes of trend lines for each factor combination.
Incorporates support for many types of models, including those in stats package (lm, glm, aov, aovlist), linear and genearalized linear mixed models (e.g., nlme, lme4, afex), ordinal-response models (e.g., ordinal, MASS), survival analysis (e.g., survival, coxme), generalized estimating equations (gee, geepack), and others. See help("models"", package="lsmeans")
Various Bayesian models (carBayes, MCMCglmm, MCMCpack) are supported by way of creating a posterior sample of least-squares means or contrasts thereof, which may then be examined using tools such as in the coda package.
Package developers may provide lsmeans support for their models by providing recover.data and lsm.basis methods. See vignette("extending", package = "lsmeans")

Installation

To install latest version from CRAN, run
```
install.packages("lsmeans")
```
Release notes for the latest CRAN version are found at https://CRAN.R-project.org/package=lsmeans/NEWS -- or do news(package = "lsmeans") for notes on the version you have installed.
To install the latest development version from Github, have the newest devtools package installed, then run
```
devtools::install_github("rvlenth/lsmeans", dependencies = TRUE)
```
For latest release notes on this development version, see the NEWS file