brms: VarCorr.brmsfit – R documentation

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VarCorr.brmsfit

Extract Variance and Correlation Components

Description

This function calculates the estimated standard deviations, correlations and covariances of the group-level terms in a multilevel model of class brmsfit. For linear models, the residual standard deviations, correlations and covariances are also returned.

Usage

## S3 method for class 'brmsfit'
VarCorr(
  x,
  sigma = 1,
  summary = TRUE,
  robust = FALSE,
  probs = c(0.025, 0.975),
  ...
)

Arguments

`x`	An object of class `brmsfit`.
`sigma`	Ignored (included for compatibility with `VarCorr`).
`summary`	Should summary statistics be returned instead of the raw values? Default is `TRUE`.
`robust`	If `FALSE` (the default) the mean is used as the measure of central tendency and the standard deviation as the measure of variability. If `TRUE`, the median and the median absolute deviation (MAD) are applied instead. Only used if `summary` is `TRUE`.
`probs`	The percentiles to be computed by the `quantile` function. Only used if `summary` is `TRUE`.
`...`	Currently ignored.

Value

A list of lists (one per grouping factor), each with three elements: a matrix containing the standard deviations, an array containing the correlation matrix, and an array containing the covariance matrix with variances on the diagonal.

Examples

## Not run: 
fit <- brm(count ~ zAge + zBase * Trt + (1+Trt|visit), 
           data = epilepsy, family = gaussian(), chains = 2)
VarCorr(fit)

## End(Not run)

brms

Bayesian Regression Models using 'Stan'

v2.15.0

GPL-2

Authors

Paul-Christian Bürkner [aut, cre], Jonah Gabry [ctb], Sebastian Weber [ctb], Andrew Johnson [ctb], Martin Modrak [ctb]

Initial release

2021-03-10