brms (version 0.9.1)

VarCorr.brmsfit: Extract variance and correlation components

Description

This function calculates the estimated standard deviations, correlations and covariances of the random-effects terms in a mixed-effects 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, estimate = "mean", as.list = TRUE,
  ...)

## S3 method for class 'brmsVarCorr':
as.data.frame(x, ...)

Arguments

x

An object of class brmsift.

sigma

Ignored (included for compatibility with VarCorr).

estimate

A character vector specifying which summary statistics (e.g., "mean", "median", "sd", or "quantile") should be calculated for the extracted parameters.

as.list

logical; Indicates if covariance and correlation matrices should be returned as lists of matrices (the default), or as 3-dimensional arrays. We recommend not to set as.list to FALSE.

...

Further arguments to be passed to the functions specified in estimate

Value

• An object of class brmsVarCorr, which is a list of lists (one per grouping factor), each containing 3 elements: a matrix containing the standard deviations, a list of correlation matrices, and a list of covariance matrices. Can be coerced to a data.frame by using the as.data.frame method.

Examples

fit <- brm(count ~ log_Age_c + log_Base4_c * Trt_c + (1+Trt_c|visit), 
             data = epilepsy, family = "poisson", chains = 1)
## return the means of random effects covariances
(vc <- VarCorr(fit))
as.data.frame(vc)

## return 2.5% and 97.5% quantiles of random effects covariances
VarCorr(fit, estimate = "quantile", probs = c(0.025, 0.975))