R package emmeans: Estimated marginal means (least-squares means)

Note

emmeans is a continuation of the package lsmeans. The latter will eventually be retired.

Features

Estimated marginal means (EMMs, previously known as least-squares means in the context of traditional regression models) are derived by using a model to make predictions over a regular grid of predictor 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 emmeans 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 EMMs, 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 emtrends 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 generalized 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 = "emmeans")

• 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 emmeans support for their models by providing recover_data and emm_basis methods. See vignette("extending", package = "emmeans")

• To install the latest development version from Github, have the newest devtools package installed, then run

devtools::install_github("rvlenth/emmeans", dependencies = TRUE,
                        build_vignettes = TRUE)

For latest release notes on this development version, see the NEWS file