lmer

0th

Percentile

Fit (Generalized) Linear Mixed-Effects Models

Fit a linear or generalized linear mixed-effects model with nested or crossed grouping factors for the random effects.

Keywords
models, methods
Usage
lmer(formula, data, family, method, control, start,
     subset, weights, na.action, offset, contrasts,
     model, ...)
lmer2(formula, data, family, method, control, start,
      subset, weights, na.action, offset, contrasts,
      model, ...)
Arguments
formula
a two-sided linear formula object describing the fixed-effects part of the model, with the response on the left of a ~ operator and the terms, separated by + operators, on the right. The vertical bar character
data
an optional data frame containing the variables named in formula. By default the variables are taken from the environment from which lmer is called.
family
a GLM family, see glm. If family is missing then a linear mixed model is fit; otherwise a generalized linear mixed model is fit.
method
a character string. For a linear mixed model the default is "REML" indicating that the model should be fit by maximizing the restricted log-likelihood. The alternative is "ML" indicating that the log-likelihood shou
control
a list of control parameters. See below for details.
start
a list of relative precision matrices for the random effects. This has the same form as the slot "Omega" in a fitted model. Only the upper triangle of these symmetric matrices should be stored.
subset, weights, na.action, offset, contrasts
further model specification arguments as in lm; see there for details.
model
logical indicating if the model component should be returned (in slot frame).
...
potentially further arguments for methods. Currently none are used.
Details

This is a revised version of the lme function from the nlme package. This version uses a different method of specifying random-effects terms and allows for fitting generalized linear mixed models as well as linear mixed models.

The lmer2 function is a development version of lmer that uses a modified internal representation of the model. Typically lmer2 is faster and more reliable than lmer. At present lmer2 can only fit linear mixed-effects models (that is, the family argument must be left unspecified) and not all the methods for "lmer" objects are defined for "lmer2" objects. In particular, there is no mcmcsamp method for "lmer2" objects.

When all the methods for the "lmer" objects and all the options for the lmer function have been duplicated for the new representation, the new representation will replace the old one and the "2" will be dropped from the name. Additional standard arguments to model-fitting functions can be passed to lmer. [object Object],[object Object],[object Object],[object Object]

Value

  • An object of class "lmer". There are many methods applicable to "lmer" objects, see the above help page.

concept

GLMM

See Also

The lmer class, lm

Aliases
  • lmer
  • lmer2
Examples
(fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
(fm2 <- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy))
anova(fm1, fm2)
Documentation reproduced from package lme4, version 0.99875-2, License: GPL version 2 or later

Community examples

Looks like there are no examples yet.