VarCorr {lme4} | R Documentation

## Extract Variance and Correlation Components

### Description

This function calculates the estimated variances, standard deviations, and correlations between the random-effects terms in a mixed-effects model, of class `merMod` (linear, generalized or nonlinear). The within-group error variance and standard deviation are also calculated.

### Usage

    ## S3 method for class 'merMod'
    VarCorr(x, sigma=1, ...)

    ## S3 method for class 'VarCorr.merMod'
    as.data.frame(x, row.names = NULL,
                  optional = FALSE, order = c("cov.last", "lower.tri"), ...)
    ## S3 method for class 'VarCorr.merMod'
    print(x, digits = max(3, getOption("digits") - 2),
          comp = "Std.Dev.", formatter = format, ...)

### Arguments

`x` | for `VarCorr`: a fitted model object, usually an object inheriting from class `merMod`. For `as.data.frame`, a `VarCorr.merMod` object returned from `VarCorr`.
`sigma` | an optional numeric value used as a multiplier for the standard deviations.
`digits` | an optional integer value specifying the number of digits
`order` | arrange data frame with variances/standard deviations first and covariances/correlations last for each random effects term (`"cov.last"`), or in the order of the lower triangle of the variance-covariance matrix (`"lower.tri"`)?
`row.names, optional` | Ignored: necessary for the `as.data.frame` method.
`...` | Ignored for the `as.data.frame` method; passed to other `print()` methods for the `print()` method.

`comp` | a `character` vector, specifying the components to be printed; simply passed to `formatVC()`.
`formatter` | a `function` for formatting the numbers; simply passed to `formatVC()`.

### Details

The `print` method for `VarCorr.merMod` objects has optional arguments `digits` (specify digits of precision for printing) and `comp`: the latter is a character vector with any combination of `"Variance"` and `"Std.Dev."`, to specify whether variances, standard deviations, or both should be printed.

### Value

An object of class `VarCorr.merMod`. The internal structure of the object is a list of matrices, one for each random effects grouping term. For each grouping term, the standard deviations and correlation matrices for each grouping term are stored as attributes `"stddev"` and `"correlation"`, respectively, of the variance-covariance matrix, and the residual standard deviation is stored as attribute `"sc"` (for `glmer` fits, this attribute stores the scale parameter of the model).

The `as.data.frame` method produces a combined data frame with one row for each variance or covariance parameter (and a row for the residual error term where applicable) and the following columns:

grp

  grouping factor

var1

  first variable

var2

  second variable (`NA` for variance parameters)

vcov

  variances or covariances

sdcor

  standard deviations or correlations

### Author(s)

This is modeled after `VarCorr` from package nlme, by Jose Pinheiro and Douglas Bates.

### See Also

`lmer`, `nlmer`

### Examples

    data(Orthodont, package="nlme")
    fm1 <- lmer(distance ~ age + (age|Subject), data = Orthodont)
    (vc <- VarCorr(fm1))  ## default print method: standard dev and corr
    ## both variance and std.dev.
    print(vc,comp=c("Variance","Std.Dev."),digits=2)
    ## variance only
    print(vc,comp=c("Variance"))
    as.data.frame(vc)
    as.data.frame(vc,order="lower.tri")

[Package lme4 version 1.1-12 Index]