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lme4: Linear Mixed-Effects Models using 'Eigen' and S4

Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

Version: 2.0-1
Depends: R (≥ 3.6), Matrix, methods, stats
Imports: MASS, Rdpack, boot, graphics, grid, lattice, minqa (≥ 1.1.15), nlme (≥ 3.1-123), nloptr (≥ 1.0.4), parallel, reformulas (≥ 0.4.3.1), rlang, splines, utils
LinkingTo: Matrix (≥ 1.5-0), Rcpp (≥ 0.10.5), RcppEigen (≥ 0.3.3.9.4)
Suggests: HSAUR3, MEMSS, car, dfoptim, gamm4, ggplot2, glmmTMB, knitr, merDeriv, mgcv, mlmRev, numDeriv, optimx (≥ 2013.8.6), pbkrtest, rmarkdown, rr2, semEff, statmod, testthat (≥ 0.8.1), tibble
Enhances: DHARMa, performance
Published: 2026-03-05
DOI: 10.32614/CRAN.package.lme4
Author: Douglas Bates ORCID iD [aut], Martin Maechler ORCID iD [aut], Ben Bolker ORCID iD [cre, aut], Steven Walker ORCID iD [aut], Rune Haubo Bojesen Christensen ORCID iD [ctb], Henrik Singmann ORCID iD [ctb], Bin Dai [ctb], Fabian Scheipl ORCID iD [ctb], Gabor Grothendieck [ctb], Peter Green ORCID iD [ctb], John Fox [ctb], Alexander Bauer [ctb], Pavel N. Krivitsky ORCID iD [ctb, cph] (shared copyright on simulate.formula), Emi Tanaka ORCID iD [ctb], Mikael Jagan ORCID iD [aut], Ross D. Boylan ORCID iD [ctb], Anna Ly ORCID iD [aut]
Maintainer: Ben Bolker <bbolker+lme4 at gmail.com>
BugReports: https://github.com/lme4/lme4/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/lme4/lme4/
NeedsCompilation: yes
Citation: lme4 citation info
Materials: NEWS, ChangeLog
In views: ClinicalTrials, Econometrics, Environmetrics, MixedModels, Psychometrics, SpatioTemporal
CRAN checks: lme4 results

Documentation:

Reference manual: lme4.html , lme4.pdf
Vignettes: Autoscaling in lme4 (source, R code)
Covariance Structures (source, R code)
lme4 performance tips (source, R code)
Computational Methods (source, R code)
Fitting Linear Mixed-Effects Models using lme4 (source, R code)
PLS vs GLS for LMMs (source, R code)

Downloads:

Package source: lme4_2.0-1.tar.gz
Windows binaries: r-devel: lme4_2.0-1.zip, r-release: lme4_2.0-1.zip, r-oldrel: lme4_2.0-1.zip
macOS binaries: r-release (arm64): lme4_2.0-1.tgz, r-oldrel (arm64): lme4_2.0-1.tgz, r-release (x86_64): lme4_2.0-1.tgz, r-oldrel (x86_64): lme4_2.0-1.tgz
Old sources: lme4 archive

Reverse dependencies:

Reverse depends: afex, agRee, arm, bapred, blme, cAIC4, carcass, CLME, eirm, gamm4, glmertree, glmmPen, GLMMRR, influence.ME, ISLET, lme4breeding, lme4GS, LMERConvenienceFunctions, lmerTest, longpower, marked, MDMR, MEMSS, merDeriv, mermboost, merTools, MIIPW, mixAK, MixRF, mlma, mlmRev, MultisiteMediation, mvMISE, panelr, pbkrtest, pedigreemm, predictmeans, predint, QualityMeasure, r2mlm, robustlmm, sae, simr, SPCDAnalyze, structree, vcPB, WebPower, WeMix
Reverse imports: abn, actuaRE, agriutilities, AgroR, ALDEx3, altmeta, ANCOMBC, ARTool, AssumpSure, attrib, autoMrP, autonomics, bayesammi, BayesCACE, BayesLN, BayesSenMC, baystability, BCClong, beezdemand, BFpack, bin2norm, blmeco, boot.pval, BradleyTerry2, breakaway, brokenstick, buildmer, CalibrationCurves, car, catalytic, ceas, censcyt, cgam, chngpt, cito, ciTools, CleaningValidation, climwin, clinicalsignificance, clintools, clustTMB, CMatching, cobin, ComBatFamQC, CompositeReliability, compositeReliabilityInNestedDesigns, confintROB, conversim, cpr, CR2, crctStepdown, CRTspat, cv, cvms, dataquieR, daySupply, DClusterm, designr, DHARMa, diagmeta, diffcyt, difR, distfreereg, doremi, doseR, dplR, dreamlet, dsBase, EdSurvey, eefAnalytics, effects, epr, epts, EQUALSTATS, EstimateBreed, evolvability, ez, faraway, fastFMM, faux, fence, finalfit, fishmethods, fullfact, galamm, gammi, geeasy, geex, gemR, GeoDiff, GimmeMyStats, glm.predict, glmm.hp, GLMMcosinor, glmmEP, glmmSeq, glmmTMB, GLMpack, gorica, GRAB, grafify, gvcR, HDANOVA, ib, iccbeta, iccmult, IDmeasurer, IMTest, inferference, INLAjoint, inti, intRvals, isni, iSTAY, IVAS, jlmerclusterperm, joineRML, jomo, jstable, JWileymisc, KenSyn, konfound, lefko3, LEGIT, likelihoodR, LKT, lmmprobe, LongDat, longsurr, LSAmitR, maaslin3, MAGNAMWAR, manymodelr, MariNET, MBECS, MCM, MDMA, MECfda, mecor, MedianaDesigner, mediation, meta, metadeconfoundR, metamicrobiomeR, metamisc, metan, metaplus, MethodCompare, MF.beta4, micemd, MIGEE, MiRKAT, misty, mixedbiastest, MixedPsy, mixpower, MLID, mlmhelpr, mlmpower, mlmtools, MLMusingR, mlVAR, MMeM, modnets, MRStdCRT, MRStdLCRT, msqrob2, MSstats, MSstatsTMT, mult.latent.reg, multid, multiDimBio, multilevelmod, multilevelTools, multisite.accuracy, multitool, multpois, muscat, mxnorm, nadir, netmediate, pamm, partR2, pastaPlot, PBImisc, pcgen, pcvr, pdR, PepSetTest, peramo, petersenlab, Phenotype, PheVis, phoenics, phyr, piecewiseSEM, plgraphics, PLmixed, pmm, POMA, PoolTestR, powerbydesign, PowRPriori, pprof, projpred, psc, psfmi, psme, PStrata, PSweight, ptmixed, PUMP, pvca, pwlmm, qape, qbrms, qra, quest, rADA, raincin, Rcmdr, RcmdrPlugin.TeachStat, readyomics, ReducedExperiment, refund, refund.shiny, reghelper, registr, regplot, REndo, repmod, reproducer, rewie, rexposome, RLRsim, rockchalk, ROTS, rpql, rptR, rqlm, rr2, RRreg, rsq, rstanarm, RStanTVA, rtpcr, RVAideMemoire, saeczi, samplr, SBMTrees, semEff, ShinyItemAnalysis, SIAmodules, SignacX, siland, SimplyAgree, skpr, smicd, smoppix, snm, SoyNAM, spAbundance, specr, splithalf, spOccupancy, spsurvey, squid, SRMERS, stabiliser, stability, standardize, statgenGxE, statgenSTA, steppedwedge, stevemisc, SumcaVer1, Surrogate, surrosurv, svycoxme, svylme, swaprinc, swCRTdesign, TcGSA, tidyILD, toscca, trace, treekoR, trouBBlme4SolveR, tukeytrend, variancePartition, varTestnlme, VCA, VetResearchLMM, vglmer, vibass, warpMix, WeightedCluster, weights, welchADF, ZLAvian
Reverse suggests: AgreementInterval, agridat, AICcmodavg, ANOM, aod, aods3, asympDiag, autoReg, bartCause, bayesDiagnostics, BayesFactor, bayestestR, BGData, bregr, brms, brolgar, broom, broom.helpers, broom.mixed, bruceR, Cardinal, cardx, catdata, catregs, clubSandwich, cocoon, codebook, connected, correlation, corrselect, ctsem, DAAG, DAGassist, DAPAR, datawizard, dlnm, doBy, dominanceanalysis, domir, dsBaseClient, dscore, easyViz, ecostats, effectsize, EgoCor, embed, emmeans, Epi, epimdr, equatiomatic, eyetrackingR, FBMS, finetune, flexmix, flextable, FRK, futurize, gamair, ggeffects, gglm, ggResidpanel, ggstatsplot, glmmFEL, glmmML, glmmsel, glmulti, gmodels, gratia, gtsummary, hamlet, HelpersMG, heritable, HLMdiag, hmclearn, hnp, HSAUR, HSAUR2, HSAUR3, huxtable, ICCbin, ILSAstats, injurytools, INLAvaan, insight, interactions, ipmr, irtrees, jmSurface, jointest, jtools, kerasnip, KFAS, kyotil, languageR, latrend, lava, lavaSearch2, LegATo, likelihoodAsy, lmeInfo, lmeresampler, lmfor, LMMstar, longmixr, lucid, lvmisc, marginaleffects, margins, MARSS, MAST, matrixset, mbest, MESS, metadat, metafor, metarep, MethComp, mice, miceadds, mitml, mixlm, mlpwr, mlr3fda, mlr3pipelines, mmrm, modelbased, modelsummary, mrap, mrIML, multcomp, multilevelcoda, MuMIn, NHSRdatasets, OlinkAnalyze, OnAge, OpenMx, ordinal, pan, papaja, parameters, pda, performance, permutes, pez, phia, polypoly, postHoc, psych, purge, R2admb, r2glmm, randRotation, RcmdrPlugin.NMBU, rdss, reformulas, report, RESI, rfars, rmcorr, RoBMA, rollout, rtables, samplingDataCRT, sandwich, SARP.compo, SASmixed, scicomptools, ScottKnott, sdmTMB, see, sense, shinybrms, simglm, SimSurvey, singcar, sjPlot, sjstats, sjtable2df, sleev, slim, sosta, SpaDES.core, spaMM, sparsenetgls, splatter, stan4bart, statlingua, summata, supernova, SynergyLMM, tableone, ThinkingGrid, tidybulk, tidyfit, tidyLPA, tidystats, tidytreatment, tram, tramME, TripleR, TukeyC, unvs.med, valueprhr, valytics, visreg, VizTest, ZIBR
Reverse enhances: biometryassist, immer, LAM, memisc, papeR, prediction, stargazer, texreg

Linking:

Please use the canonical form https://CRAN.R-project.org/package=lme4 to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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