GLMM-class {lme4}R Documentation

Class "GLMM"

Description

A fitted generalized linear mixed model.

Details

Many methods for the "GLMM" class simply recall the generic on as(object, "lme") which, in turn, often calls the generic on the "rep" component of the first argument. Thus the methods actually are applied to an object of the "lme" or "ssclme" class.

Objects from the Class

Objects are usually created by calls to the constructor function GLMM. They also can be created by calls of the form new("GLMM", ...).

Slots

family:
The family of functions defining the generalized linear model. See family for details.
logLik:
the "numeric" value of the log-likelihood.
fixef:
A "numeric" vector of fixed-effects parameters.
call:
A copy of the function call that created the object.
facs:
A list of (possibly reordered) grouping factors associated with the random effects.
x:
If the optional argument x to lme is TRUE, a list of model matrices associated with the random effects, and the fixed effects with the response appended. Otherwise, an empty list.
model:
The model frame (of class "data.frame") for the model or, if the optional argument model to lme is FALSE, an empty frame.
REML:
A "logical" indicator of the model having been fit according to the REML criterion.
rep:
An "ssclme" object representing the fitted model.
fitted:
A "numeric" vector of fitted values.
residuals:
A "numeric" vector of raw residuals.

Extends

Class "lme", directly.

Methods

VarCorr
signature(x = "GLMM"): Extract the variances, standard deviations, and correlations of the random effects.
anova
signature(object = "GLMM"): Perform an analysis of variance.
coef
signature(object = "GLMM"): Extract the parameters that determine the relative precision matrices. The optional argument unconst determines if the constrained or unconstrained parameterization is used.
deviance
signature(object = "GLMM"): Extract the deviance as a numeric scalar. The optional argument REML determines if the REML or ML criterion is used.
fitted
signature(object = "GLMM"): Extract the fitted values as a numeric vector.
fixef
signature(object = "GLMM"): Extract the fixed effects coefficients as a named numeric vector
formula
signature(x = "GLMM"): Extract the formula of the response and the fixed effects.
logLik
signature(object = "GLMM"): Extract the log-likelihood.
plot
signature(x = "GLMM"):
ranef
signature(object = "GLMM"): Extact the random effects as a named list of numeric matrices.
residuals
signature(object = "GLMM"): Extract the residuals as a numeric vector.
show
signature(object = "GLMM"): Print a concise description of the object.
summary
signature(object = "GLMM"): Create a summary object of class "summary.lme".
update
signature(object = "GLMM"): Create an updated fitted model.
vcov
signature(object = "GLMM"): Extract the variances and covariances of the fixed-effects parameter estimates.

See Also

GLMM, lme-class, ssclme-class


[Package lme4 version 0.6-9 Index]