Package index • lme4

All functions

Arabidopsis: Arabidopsis clipping/fertilization data
Dyestuff Dyestuff2: Yield of dyestuff by batch
GHrule(): Univariate Gauss-Hermite quadrature rule
GQdk() GQN: Sparse Gaussian / Gauss-Hermite Quadrature grid
InstEval: University Lecture/Instructor Evaluations by Students at ETH
NelderMead(): Class "NelderMead" of Nelder-Mead optimizers and its Generator
Nelder_Mead(): Nelder-Mead Optimization of Parameters, Possibly (Box) Constrained
Pastes: Paste strength by batch and cask
Penicillin: Variation in penicillin testing
VarCorr(<merMod>) as.data.frame(<VarCorr.merMod>) print(<VarCorr.merMod>): Extract Variance and Correlation Components
VerbAgg: Verbal Aggression item responses
allFit(): Refit a fitted model with all available optimizers to check convergence
bootMer(): Model-based (Semi-)Parametric Bootstrap for Mixed Models
cake: Breakage Angle of Chocolate Cakes
cbpp: Contagious bovine pleuropneumonia
cbpp2: Contagious bovine pleuropneumonia (extended version)
checkConv(): Extended Convergence Checking
confint(<merMod>) confint(<thpr>): Compute Confidence Intervals for Parameters of a [ng]lmer Fit
convergence: Assessing Convergence for Fitted Models
culcitalogreg: Coral-eating seastar Culcita novaeguineae data (binary predation version)
culcitalvolume: Coral-eating seastar Culcita novaeguineae data (volume loss version)
devcomp(): Extract the deviance component list
devfun2(): Deviance Function in Terms of Standard Deviations/Correlations
drop1(<merMod>): Drop all possible single fixed-effect terms from a mixed effect model
dummy(): Dummy variables (experimental)
factorize(): Attempt to convert grouping variables to factors
fixef(<merMod>): Extract fixed-effects estimates
fortify.merMod() getData(<merMod>): add information to data based on a fitted model
getME(): Extract or Get Generalized Components from a Fitted Mixed Effects Model
glmFamily-class: Class "glmFamily" - a reference class for family
glmFamily(): Generator object for the glmFamily class
glmer(): Fitting Generalized Linear Mixed-Effects Models
glmer.nb(): Fitting Negative Binomial GLMMs
glmerLaplaceHandle(): Handle for glmerLaplace
golden(): Class "golden" and Generator for Golden Search Optimizer Class
gopherdat2: Gopher tortoises shell remains
grouseticks: Data on red grouse ticks from Elston et al. 2001
hatvalues(<merMod>): Diagonal elements of the hat matrix
influence(<merMod>) cooks.distance(<influence.merMod>) dfbeta(<influence.merMod>) dfbetas(<influence.merMod>): Influence Diagnostics for Mixed-Effects Models
isREML() isLMM() isNLMM() isGLMM(): Check characteristics of models
isSingular(): Test Fitted Model for (Near) Singularity
lmList(): Fit List of lm or glm Objects with a Common Model
lmList4-class show,lmList4-method: Class "lmList4" of 'lm' Objects on Common Model
glmResp-class lmerResp-class lmResp-class nlsResp-class: Reference Classes for Response Modules, "(lm|glm|nls|lmer)Resp"
lmResp(): Generator objects for the response classes
lme4 lme4-package: Linear, generalized linear, and nonlinear mixed models
lme4_testlevel(): Detect testing level for lme4 examples and tests
lmer(): Fit Linear Mixed-Effects Models
lmerControl() glmerControl() nlmerControl() .makeCC(): Control of Mixed Model Fitting
anova(<merMod>) as.function(<merMod>) coef(<merMod>) deviance(<merMod>) REMLcrit() extractAIC(<merMod>) family(<merMod>) formula(<merMod>) fitted(<merMod>) logLik(<merMod>) nobs(<merMod>) ngrps(<merMod>) terms(<merMod>) model.frame(<merMod>) model.matrix(<merMod>) print(<merMod>) update(<merMod>) weights(<merMod>): Class "merMod" of Fitted Mixed-Effect Models
merPredD-class: Class "merPredD" - a Dense Predictor Reference Class
merPredD(): Generator object for the merPredD class
mkMerMod(): Create a 'merMod' Object
mkNewReTrms(): Make new random effect terms for prediction
mkRespMod(): Create an lmerResp, glmResp or nlsResp instance
mkParsTemplate() mkDataTemplate(): Make templates suitable for guiding mixed model simulations
mkVarCorr(): Make Variance and Correlation Matrices from theta
lFormula() mkLmerDevfun() optimizeLmer() glFormula() mkGlmerDevfun() optimizeGlmer() updateGlmerDevfun(): Modular Functions for Mixed Model Fits
namedList(): Self-naming list function
ngrps(): Number of Levels of a Factor or a "merMod" Model
nlformula(): Manipulate a Nonlinear Model Formula
nlmer(): Fitting Nonlinear Mixed-Effects Models
nloptwrap() nlminbwrap(): Wrappers for additional optimizers
plot(<merMod>) qqmath(<merMod>): Diagnostic Plots for 'merMod' Fits
xyplot(<thpr>) densityplot(<thpr>) splom(<thpr>): Mixed-Effects Profile Plots (Regular / Density / Pairs)
predict(<merMod>): Predictions from a model at new data values
profile(<merMod>) as.data.frame(<thpr>) log(<thpr>) logProf() varianceProf(): Profile method for merMod objects
mcmcsamp pvalues: Getting p-values for fitted models
ranef(<merMod>) dotplot(<ranef.mer>) qqmath(<ranef.mer>) as.data.frame(<ranef.mer>): Extract the modes of the random effects
rePCA(): PCA of random-effects covariance matrix
rePos-class: Class "rePos"
rePos(): Generator object for the rePos (random-effects positions) class
refit(): Refit a (merMod) Model with a Different Response
refitML(): Refit a Model by Maximum Likelihood Criterion
subbars() nobars() findbars() mkReTrms() isNested(): (deprecated) formula-processing functions
residuals(<merMod>) residuals(<lmResp>) residuals(<glmResp>): residuals of merMod objects
salamander: Mountain dusky salamander mating
schizophrenia: National Institute of Mental Health Schizophrenia Collaborative Study
sigma(<merMod>): Extract Residual Standard Deviation 'Sigma'
simulate(<formula>): A simulate Method for formula objects that dispatches based on the Left-Hand Side
simulate(<merMod>) .simulateFun(): Simulate Responses From merMod Object
sleepstudy: Reaction times in a sleep deprivation study
summary(<merMod>) print(<summary.merMod>): Summary for a [ng]lmer Fit
toenail: Toenail onychomycosis data from dermatophyte infections
troubleshooting: Troubleshooting
llikAIC() methTitle() .prt.methTit() .prt.family() .prt.resids() .prt.call() .prt.aictab() .prt.grps() .prt.warn() .prt.VC() formatVC(): Print and Summary Method Utilities for Mixed Effects
mlist2vec() vec2mlist() vec2STlist() sdcor2cov() cov2sdcor() Vv_to_Cv() Sv_to_Cv() Cv_to_Vv() Cv_to_Sv(): Convert between representations of (co-)variance structures
vcov(<merMod>): Covariance matrix of estimated parameters