Package index • emmeans

Overview

emmeans-package: Estimated marginal means (aka Least-squares means)

Estimation of marginal means and trends

ref_grid(): Create a reference grid from a fitted model

emmeans(): Estimated marginal means (Least-squares means)

emtrends(): Estimated marginal means of linear trends

lsmeans() lstrends() lsmip() lsm() lsmobj() lsm.options() get.lsm.option(): Wrappers for alternative naming of EMMs

qdrg(): Quick and dirty reference grid

Follow-up analyses

contrast() pairs(<emmGrid>) coef(<emmGrid>) weights(<emmGrid>): Contrasts and linear functions of EMMs

eff_size(): Calculate Cohen effect sizes and confidence bounds thereof

joint_tests() make.meanint() meanint() make.symmint() symmint(): Compute joint tests of the terms in a model

mvcontrast(): Multivariate contrasts

pairwise.emmc() revpairwise.emmc() tukey.emmc() poly.emmc() opoly.emmc() trt.vs.ctrl.emmc() trt.vs.ctrl1.emmc() trt.vs.ctrlk.emmc() dunnett.emmc() eff.emmc() del.eff.emmc() consec.emmc() mean_chg.emmc() helmert.emmc() nrmlz.emmc() wtcon.emmc() identity.emmc(): Contrast families

Summaries

summary(<emmGrid>) confint(<emmGrid>) test() predict(<emmGrid>) as.data.frame(<emmGrid>) `[`(<summary_emm>): Summaries, predictions, intervals, and tests for emmGrid objects

hpd.summary(): Summarize an emmGrid from a Bayesian model

untidy: Dare to be un-"tidy"!

Modifying objects

comb_facs() split_fac() add_grouping() add_submodels() permute_levels(): Manipulate factors in a reference grid

rbind(<emmGrid>) `+`(<emmGrid>) `[`(<emmGrid>) head(<emmGrid>) tail(<emmGrid>) subset(<emmGrid>) rbind(<emm_list>) rbind(<summary_emm>) force_regular(): Combine or subset emmGrid objects

regrid(): Reconstruct a reference grid with a new transformation or simulations

mvregrid(): Multivariate regridding

update(<emmGrid>) `levels<-`(<emmGrid>) update(<summary_emm>): Update an emmGrid object

Displays

cld(<emmGrid>) cld(<emm_list>): Compact letter displays

emmip() emmip_ggplot() emmip_lattice(): Interaction-style plots for estimated marginal means

plot(<emmGrid>) plot(<summary_emm>): Plot an emmGrid or summary_emm object

pwpm(): Pairwise P-value matrix (plus other statistics)

pwpp(): Pairwise P-value plot

Data sets

auto.noise: Auto Pollution Filter Noise

feedlot: Feedlot data

fiber: Fiber data

MOats: Oats data in multivariate form

neuralgia: Neuralgia data

nutrition: Nutrition data

oranges: Sales of oranges

pigs: Effects of dietary protein on free plasma leucine concentration in pigs

ubds: Unbalanced dataset

Structures

emmGrid-class: The emmGrid class

emmobj(): Construct an emmGrid object from scratch

contrast(<emm_list>) pairs(<emm_list>) test(<emm_list>) confint(<emm_list>) plot(<emm_list>) coef(<emm_list>) linfct(<emm_list>) str(<emm_list>) summary(<emm_list>) print(<emm_list>) as.data.frame(<emm_list>) as.data.frame(<summary_eml>): The emm_list class

Utilities

emm() as.glht(): Support for multcomp::glht

emm_example(): Run or list additional examples

emm_options() get_emm_option() with_emm_options() emm_defaults: Set or change emmeans options

str(<emmGrid>) print(<emmGrid>) vcov(<emmGrid>) linfct(): Miscellaneous methods for emmGrid objects

make.tran() inverse(): Response-transformation extensions

Convert to outside formats

as.list(<emmGrid>) as.emm_list() as.emmGrid(): Convert to and from emmGrid objects

as.mcmc(<emmGrid>) as.mcmc(<emm_list>) as.mcmc.list(<emmGrid>) as.mcmc.list(<emm_list>): Support for MCMC-based estimation

xtable(<emmGrid>) xtable(<summary_emm>) print(<xtable_emm>): Using xtable for EMMs

Models and extending

models: Models supported in emmeans

recover_data() emm_basis() .emm_register() .std.link.labels() .combine.terms() .aovlist.dffun() .cmpMM() .get.excl() .get.offset() .my.vcov() .all.vars() .diag() .num.key() .emm_vignette() .hurdle.support() .zi.support(): Support functions for model extensions