summary.brms_mmrm_transform_marginal: Summarize marginal transform.

In brms.mmrm: Bayesian MMRMs using 'brms'

Summarize marginal transform.

Description

Summarize a transformation from model parameters to marginal means.

Usage

## S3 method for class 'brms_mmrm_transform_marginal'
summary(object, message = TRUE, ...)

Arguments

object	The brm_transform_marginal() matrix to summarize.
message	TRUE to print an informative message about the archetype and invisibly return a character vector of equations. FALSE to forgo verbose messages and non-invisibly return the equations.
...	Not used, but required for S3 methods that inherit from the base generic summary().

Value

Return a character vector with linear equations that map model parameters to marginal means. If the message argument is TRUE (default) then this character vector is returned invisibly and a verbose description of the equations is printed.

Examples

set.seed(0L)
data <- brm_data(
  data = brm_simulate_simple()$data,
  outcome = "response",
  group = "group",
  time = "time",
  patient = "patient",
  reference_group = "group_1",
  reference_time = "time_1"
)
formula <- brm_formula(
  data = data,
  baseline = FALSE,
  baseline_time = FALSE
)
transform <- brm_transform_marginal(data = data, formula = formula)
equations <- summary(transform)
print(equations)
summary(transform, message = FALSE)
class(transform)
print(transform)

brms.mmrm documentation built on Oct. 3, 2024, 1:08 a.m.