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Mixed Effects

Linear mixed-effects models

Classes

LinearMixedModel Linear mixed-effects model class

Functions

fitlmeFit linear mixed-effects model
fitlmematrixFit linear mixed-effects model
dispDisplay linear mixed-effects model
predict Predict response of linear mixed-effects model
random Generate random responses from fitted linear mixed-effects model
fixedEffectsEstimates of fixed effects and related statistics
randomEffects Estimates of random effects and related statistics
designMatrixFixed- and random-effects design matrices
fittedFitted responses from a linear mixed-effects model
responseResponse vector of the linear mixed-effects model
anovaAnalysis of variance for linear mixed-effects model
coefCI Confidence intervals for coefficients of linear mixed-effects model
coefTestHypothesis test on fixed and random effects of linear mixed-effects model
compareCompare linear mixed-effects models
covarianceParametersExtract covariance parameters of linear mixed-effects model
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
plotResidualsPlot residuals of linear mixed-effects model
residualsResiduals of fitted linear mixed-effects model

Examples and How To

Prepare Data for Linear Mixed-Effects Models

Store data in the correct form for fitting a linear mixed-effects model.

Relationship Between Formula and Design Matrices

Understand the relationship between a model formula and the design matrices in linear mixed-effects models.

Linear Mixed-Effects Model Workflow

This example shows how to fit and analyze a linear mixed-effects model (LME).

Fit Mixed-Effects Spline Regression

This example shows how to fit a mixed-effects linear spline model.

Concepts

Linear Mixed-Effects Models

Linear mixed-effects models are extensions of linear regression models for data that are collected and summarized in groups.

Estimating Parameters in Linear Mixed-Effects Models

The two most commonly used approaches to parameter estimation in linear mixed-effects models are maximum likelihood and restricted maximum likelihood methods.

Wilkinson Notation

Wilkinson notation provides a way to describe regression and repeated measures models without specifying coefficient values.

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