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lme4 (version 1.1-35.1)

Linear Mixed-Effects Models using 'Eigen' and S4

Description

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".

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Install

install.packages('lme4')

Monthly Downloads

573,149

Version

1.1-35.1

License

GPL (>= 2)

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Repository

https://github.com/lme4/lme4/

Maintainer

Ben Bolker

Last Published

November 5th, 2023

Functions in lme4 (1.1-35.1)

Model-based (Semi-)Parametric Bootstrap for Mixed Models

Compute Confidence Intervals for Parameters of a [ng]lmer Fit

Extended Convergence Checking

Assessing Convergence for Fitted Models

Extract the deviance component list

Breakage Angle of Chocolate Cakes

Contagious bovine pleuropneumonia

Verbal Aggression item responses

Refit a fitted model with all available optimizers

Deviance Function in Terms of Standard Deviations/Correlations

glmFamily-class

Class "glmFamily" - a reference class for family

add information to data based on a fitted model

Generator object for the glmFamily class

expandDoubleVerts

Expand terms with '||' notation into separate '|' terms

Extract or Get Generalized Components from a Fitted Mixed Effects Model

Check characteristics of models

Is f1 nested within f2?

Test Fitted Model for (Near) Singularity

glmerLaplaceHandle

Handle for glmerLaplace

influence.merMod

Influence Diagnostics for Mixed-Effects Models

Extract fixed-effects estimates

Determine random-effects expressions from a formula

Dummy variables (experimental)

hatvalues.merMod

Diagonal elements of the hat matrix

Attempt to convert grouping variables to factors

Class "golden" and Generator for Golden Search Optimizer Class

Data on red grouse ticks from Elston et al. 2001

Drop all possible single fixed-effect terms from a mixed effect model

Fitting Generalized Linear Mixed-Effects Models

Fitting Negative Binomial GLMMs

Linear, generalized linear, and nonlinear mixed models

Detect testing level for lme4 examples and tests

Fit List of lm or glm Objects with a Common Model

Control of Mixed Model Fitting

Fit Linear Mixed-Effects Models

Reference Classes for Response Modules, "(lm|glm|nls|lmer)Resp"

Class "merPredD" - a Dense Predictor Reference Class

Generator objects for the response classes

Class "merMod" of Fitted Mixed-Effect Models

Class "lmList4" of 'lm' Objects on Common Model

Number of Levels of a Factor or a "merMod" Model

Manipulate a Nonlinear Model Formula

Self-naming list function

Generator object for the merPredD class

Modular Functions for Mixed Model Fits

mkSimulateTemplate

Make templates suitable for guiding mixed model simulations

Make Variance and Correlation Matrices from theta

Make Random Effect Terms: Create Z, Lambda, Lind, etc.

Create a 'merMod' Object

Create an lmerResp, glmResp or nlsResp instance

Mixed-Effects Profile Plots (Regular / Density / Pairs)

Diagnostic Plots for 'merMod' Fits

Extract the modes of the random effects

Getting p-values for fitted models

PCA of random-effects covariance matrix

Wrappers for additional optimizers

Fitting Nonlinear Mixed-Effects Models

profile-methods

Profile method for merMod objects

Predictions from a model at new data values

Omit terms separated by vertical bars in a formula

simulate.merMod

Simulate Responses From merMod Object

Class "rePos"

simulate.formula

A simulate Method for formula objects that dispatches based on the Left-Hand Side

Refit a (merMod) Model with a Different Response

Refit a Model by Maximum Likelihood Criterion

residuals.merMod

residuals of merMod objects

Reaction times in a sleep deprivation study

Generator object for the rePos (random-effects positions) class

Extract Residual Standard Deviation 'Sigma'

"Sub[stitute] Bars"

Convert between representations of (co-)variance structures

Print and Summary Method Utilities for Mixed Effects

troubleshooting

Troubleshooting

Univariate Gauss-Hermite quadrature rule

University Lecture/Instructor Evaluations by Students at ETH

Sparse Gaussian / Gauss-Hermite Quadrature grid

Arabidopsis clipping/fertilization data

NelderMead-class

Class "NelderMead" of Nelder-Mead optimizers and its Generator

Paste strength by batch and cask

Variation in penicillin testing

Extract Variance and Correlation Components

Nelder-Mead Optimization of Parameters, Possibly (Box) Constrained

Yield of dyestuff by batch