lmer {lme4}R Documentation

Fit linear mixed-effects models

Description

This generic function fits a linear mixed-effects model with nested or crossed grouping factors for the random effects.

Usage

lmer(formula, data, family,
     method = c("REML", "ML", "PQL", "Laplace", "AGQ"),...)

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 "|" separates an expression for a model matrix and a grouping factor.
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 should be maximized. (This method is sometimes called "full" maximum likelihood.) For a generalized linear mixed model the criterion is always the log-likelihood but this criterion does not have a closed form expression and must be approximated. The default approximation is "PQL" or penalized quasi-likelihood. Alternatives are "Laplace" or "AGQ" indicating the Laplacian and adaptive Gaussian quadrature approximations respectively. The "PQL" method is fastest but least accurate. The "Laplace" method is intermediate in speed and accuracy. The "AGQ" method is the most accurate but can be considerably slower than the others.
... Optional 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.

Additional standard arguments to model-fitting functions can be passed to lmer.

subset
an optional expression indicating the subset of the rows of data that should be used in the fit. This can be a logical vector, or a numeric vector indicating which observation numbers are to be included, or a character vector of the row names to be included. All observations are included by default.
na.action
a function that indicates what should happen when the data contain NAs. The default action (na.fail) causes lme to print an error message and terminate if there are any incomplete observations.
control
a list of control values for the estimation algorithm to replace the default values returned by the function lmerControl. Defaults to an empty list.
model, x
logicals. If TRUE the corresponding components of the fit (the model frame, the model matrices) are returned.

Value

An lme-class{lmer} object.

See Also

lmer-class, lm

Examples

(fm1 <- lmer(decrease ~ treatment + (1|rowpos) + (1|colpos),
             OrchardSprays))

[Package lme4 version 0.95-8 Index]