Extract the group-level ('random') effects of each level
from a brmsfit object.
Usage
# S3 method for brmsfit
ranef(object, summary = TRUE, robust = FALSE,
probs = c(0.025, 0.975), old = FALSE, estimate = c("mean", "median"),
var = FALSE, ...)
Arguments
object
An object of class brmsfit.
summary
Should summary statistics
(i.e. means, sds, and 95% intervals) 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 deivation (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.
old
Logical; indicates if the old implementation
of this method (prior to version 1.7.0) should be used.
Defaults to FALSE.
estimate
(Deprecated) The point estimate to be calculated
for the group-level effects, either "mean" or "median".
var
(Deprecated) Logical; indicates if the covariance matrix
for each group-level effects should be computed.
...
Further arguments to be passed to the function
specified in estimate.
Value
If old is FALSE: A list of arrays
(one per grouping factor). If summary is TRUE,
names of the first dimension are the factor levels and names
of the third dimension are the group-level effects.
If summary is FALSE, names of the second dimension
are the factor levels and names of the third dimension are the
group-level effects.
If old is TRUE: A list of matrices (one per grouping factor),
with factor levels as row names and group-level effects as column names.
# NOT RUN {fit <- brm(count ~ log_Age_c + log_Base4_c * Trt_c + (1+Trt_c|visit),
data = epilepsy, family = gaussian(), chains = 2)
ranef(fit)
# }# NOT RUN {# }