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

merMod-class {lme4}

R Documentation

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, ...)
## 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, ...)
## 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 R object of class `merMod`, i.e., as resulting from `lmer()`, or `glmer()`, etc.
`x`	an R object of class `merMod` or `summary.merMod`, respectively, the latter resulting from `summary(<merMod>)`.
`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 effects, whose likelihoods are not directly comparable.
`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 should be printed.
`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 `getME(.,"RX")`). The default is to to use the Hessian whenever the fixed effect parameters are arguments to the deviance function (i.e. for GLMMs with `nAGQ>0`), and to use `getME(.,"RX")` whenever the fixed effect parameters are profiled out (i.e. for GLMMs with `nAGQ==0` or LMMs). `use.hessian=FALSE` is backward-compatible with older versions of `lme4`, but may give less accurate SE estimates when the estimates of the fixed-effect (see `getME(.,"beta")`) and random-effect (see `getME(.,"theta")`) parameters are correlated.
`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.

S3 methods

The following S3 methods with arguments given above exist (this list is currently not complete):

summary:: Computes and returns a list of summary statistics of the fitted model, the amount of output can be controlled via the print method, see also summary.
print.summary:: Controls the output for the summary method.
vcov:: Calculate variance-covariance matrix of the fixed effect terms, see also vcov.
anova:: returns the sequential decomposition of the contributions of fixed-effects terms or, for multiple arguments, model comparison statistics. For objects of class lmerMod the default behavior is to refit the models with LM if fitted with REML = TRUE, this can be controlled via the refit argument. See also anova.

Examples

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

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

[Package lme4 version 1.1-5 Index]