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Showing content from https://cran.r-project.org/web/packages/rms/../parameters/../emmeans/index.html below:

CRAN: Package emmeans

emmeans: Estimated Marginal Means, aka Least-Squares Means

Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.

Version: 1.11.2 Depends: R (≥ 4.1.0) Imports: estimability (≥ 1.4.1), graphics, methods, mvtnorm, numDeriv, stats, utils Suggests: bayesplot, bayestestR, biglm, brms, car, coda (≥ 0.17), compositions, ggplot2, knitr, lattice, lme4, lmerTest (≥ 2.0.32), logspline, MASS, mediation, mgcv, multcomp, multcompView, MuMIn, nlme, ordinal (≥ 2014.11-12), pbkrtest (≥ 0.4-1), rmarkdown, rsm, sandwich, scales, splines, testthat, tibble, xtable (≥ 1.8-2) Enhances: CARBayes, coxme, gee, geepack, MCMCglmm, MCMCpack, mice, nnet, pscl, rstanarm, sommer, survival Published: 2025-07-11 DOI: 10.32614/CRAN.package.emmeans Author: Russell V. Lenth [aut, cre, cph], Balazs Banfai [ctb], Ben Bolker [ctb], Paul Buerkner [ctb], Iago Giné-Vázquez [ctb], Maxime Herve [ctb], Maarten Jung [ctb], Jonathon Love [ctb], Fernando Miguez [ctb], Julia Piaskowski [ctb], Hannes Riebl [ctb], Henrik Singmann [ctb] Maintainer: Russell V. Lenth <russell-lenth at uiowa.edu> BugReports: https://github.com/rvlenth/emmeans/issues License: GPL-2 | GPL-3 URL: https://rvlenth.github.io/emmeans/,https://rvlenth.github.io/emmeans/ NeedsCompilation: no Materials: README NEWS In views: MixedModels CRAN checks: emmeans results Documentation: Reference manual: emmeans.pdf Vignettes: A quick-start guide for emmeans (source, R code)
FAQs for emmeans (source, R code)
Basics of EMMs (source, R code)
Comparisons and contrasts (source, R code)
Confidence intervals and tests (source, R code)
Interaction analysis in emmeans (source, R code)
Working with messy data (source, R code)
Models supported by emmeans (source)
Prediction in emmeans (source, R code)
Re-engineering CLDs (source, R code)
Sophisticated models in emmeans (source, R code)
Transformations and link functions (source, R code)
Utilities and options (source, R code)
Index of vignette topics (source)
Explanations supplement (source, R code)
For developers: Extending emmeans (source, R code)
Downloads: Reverse dependencies: Reverse depends: AOboot, LabApplStat, lsmeans, pubh, RRphylo Reverse imports: agriTutorial, agriutilities, AgroR, ARTool, augmentedRCBD, biometryassist, bruceR, CANE, dataquieR, distdichoR, eda4treeR, FactoMineR, grafify, healthequal, ibd, inti, iNZightPlots, jmv, junco, JWileymisc, LinkHD, LongDat, mbbe, mi4p, multid, multilevelcoda, OlinkAnalyze, peramo, piecewiseSEM, pwr4exp, QuAnTeTrack, qusage, rbiom, rtpcr, SDLfilter, seedreg, SimplyAgree, statforbiology, statgenGxE, statgenSTA, StroupGLMM, Superpower, tern, tern.gee, tern.mmrm Reverse suggests: afex, agridat, asremlPlus, bayestestR, BrailleR, brms, brms.mmrm, broom, broom.helpers, cardx, catregs, catseyes, datawizard, DoseFinding, effectsize, estimatr, fddm, fixest, GGally, ggeffects, ggstats, GLMMadaptive, glmmSeq, glmmTMB, gtsummary, insight, lavaSearch2, LegATo, logistf, marginaleffects, metafor, mmrm, modelbased, multpois, nlraa, papaja, parameters, PowerTOST, r2rtf, rbmi, rempsyc, report, RoBMA, robustlmm, rsm, rstatix, RVAideMemoire, s20x, sdmTMB, see, semTools, spmodel, standardize, structToolbox, survstan, tidybayes, tidystats Reverse enhances: mclogit, spaMM Linking:

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