lme4 (version 1.1-5)

merMod-class: Class "merMod" of Fitted Mixed-Effect Models

Description

A mixed-effects model is represented as a merPredD object and a response module of a class that inherits from class lmResp. A model with a lmerResp response has class lmerMod; a glmResp response has class glmerMod; and a nlsResp response has class nlmerMod.

Usage

## S3 method for class 'merMod':
anova(object, ..., refit = TRUE, model.names=NULL)
## S3 method for class 'merMod':
terms(x, fixed.only = TRUE, \dots)
## S3 method for class 'merMod':
vcov(object, correlation = TRUE, sigm = sigma(object),
use.hessian = NULL, ...)

## S3 method for class 'merMod': print(x, digits = max(3, getOption("digits") - 3), correlation = NULL, symbolic.cor = FALSE, signif.stars = getOption("show.signif.stars"), ranef.comp = "Std.Dev.", ...)

## S3 method for class 'merMod': summary(object, correlation = , use.hessian = NULL, \dots) ## S3 method for class 'summary.merMod': print(x, digits = max(3, getOption("digits") - 3), correlation = NULL, symbolic.cor = FALSE, signif.stars = getOption("show.signif.stars"), ranef.comp = c("Variance", "Std.Dev."), show.resids = TRUE, ...) ## S3 method for class 'merMod': weights(object, type = c("prior", "working"), ...)

Arguments

object
an Robject of class merMod, i.e., as resulting from lmer(), or glmer(), etc.
x
an Robject of class merMod or summary.merMod, respectively, the latter resulting from summary().
refit
logical indicating if objects of class lmerMod should be refitted with ML before comparing models. The default is TRUE to prevent the common mistake of inappropriately comparing REML-fitted models with different fixed
model.names
character vectors of model names to be used in the anova table.
fixed.only
logical indicating if only the fixed effects terms are sought, defaults to true. If false, all terms, including random ones are returned.
correlation
(logical) for vcov, indicates whether the correlation matrix as well as the variance-covariance matrix is desired; for print.summary.merMod, indicates whether the correlation matrix of the fixed-effects parameters sho
use.hessian
(logical) indicates whether to use the finite-difference Hessian of the deviance function to compute standard errors of the fixed effects, rather estimating based on internal information about the inverse of the model matrix (see
sigm
the residual standard error; by default sigma(object).
digits
number of significant digits for printing
symbolic.cor
should a symbolic encoding of the fixed-effects correlation matrix be printed? If so, the symnum function is used.
signif.stars
(logical) should significance stars be used?
ranef.comp
character vector of length one or two, indicating if random-effects parameters should be reported on the variance and/or standard deviation scale.
show.resids
should the quantiles of the scaled residuals be printed?
type
type of weights to be returned; either "prior" for the initially supplied weights or "working" for the weights at the final iteration of the penalized iteratively reweighted least squares algorithm.
...
potentially further arguments passed from other methods.

Objects from the Class

Objects of class merMod are created by calls to lmer, glmer or nlmer.

See Also

lmer, glmer, nlmer, merPredD, lmerResp, glmResp, nlsResp

Examples

Run this code
showClass("merMod")
methods(class="merMod")## over 30  (S3) methods available

## -> example(lmer)  for an example of vcov.merMod()

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