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emmeans: Estimated Marginal Means, aka Least-Squares Means (original) (raw)

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: 1.10.6
Depends: R (≥ 4.1.0)
Imports: estimability (≥ 1.4.1), graphics, methods, numDeriv, stats, utils, mvtnorm
Suggests: bayesplot, bayestestR, biglm, brms, car, coda (≥ 0.17), compositions, ggplot2, lattice, logspline, mediation, mgcv, multcomp, multcompView, nlme, ordinal (≥ 2014.11-12), pbkrtest (≥ 0.4-1), lme4, lmerTest (≥ 2.0.32), MASS, MuMIn, rsm, knitr, rmarkdown, sandwich, scales, splines, testthat, tibble, xtable (≥ 1.8-2)
Enhances: CARBayes, coxme, gee, geepack, MCMCglmm, MCMCpack, mice, nnet, pscl, rstanarm, sommer, survival
Published: 2024-12-12
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
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, dataquieR, distdichoR, eda4treeR, FactoMineR, grafify, healthequal, ibd, inti, iNZightPlots, jmv, JWileymisc, LinkHD, LongDat, mbbe, mi4p, multid, multilevelcoda, OlinkAnalyze, peramo, piecewiseSEM, pwr4exp, 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, 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

Linking:

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