lme-class {lme4} | R Documentation

## Class "lme"

### Description

A linear mixed-effects model.

### Objects from the Class

Objects can be created by calls of the form `new("lme", ...)`.

### Slots

`reStruct`:
  Object of class `"reStruct"`, the random-effects structure for the model.
`frame`:
  Object of class `"data.frame"`, the model.frame used to fit the model.
`na.action`:
  Object of class `"ANY"`, the `na.action` argument used when creating the `model.frame`.
`fitted`:
  Object of class `"numeric"`, the current fitted values.
`call`:
  Object of class `"call"`, the function call used to create the object.

### Extends

Class `"lme"`, directly.

### Methods

VarCorr
  `signature(x = "lme")`: extract variance and correlation components.
anova
  `signature(object = "lme")`: calculate analysis of variance tables for linear mixed effects models.
coef
  `signature(object = "lme")`: extract the random effects parameters for the model.
fitted
  `signature(object = "lme")`: extract the fitted values.
fixef
  `signature(object = "lme")`: extract the fixed effects parameters.
formula
  `signature(x = "lme")`: extract the fixed effects formula.
getResponse
  `signature(object = "lme")`: extract the response.
intervals
  `signature(object = "lme")`: calculate confidence intervals.
logLik
  `signature(object = "lme")`: calculate the log-likelihood or log-restricted-likelihood for the model
plot
  `signature(x = "lme")`: plot the fitted model.
ranef
  `signature(object = "lme")`: calculate the random-effects coefficients
residuals
  `signature(object = "lme")`: calculate the residuals from the model fit.
show
  `signature(object = "lme")`: show the object.
summary
  `signature(object = "lme")`: summarize the object.
update
  `signature(object = "lme")`: update the model fit.

### Author(s)

Saikat DebRoy saikat@stat.wisc.edu and Douglas Bates bates@stat.wisc.edu

### Examples

    library(lme4)
    data(bdf)
    # This returns an object of class lme
    fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf,
              random = ~ IQ.ver.cen | schoolNR)
    fm

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