mediation() is a short summary for multivariate-response
mediation-models.
mediation(x, ...)# S3 method for brmsfit
mediation(x, treatment, mediator, prob = 0.9, typical = "median", ...)
A stanreg, stanfit, or brmsfit object.
Not used.
Character, name of the treatment variable (or direct effect)
in a (multivariate response) mediator-model. If missing, mediation()
tries to find the treatment variable automatically, however, this may fail.
Character, name of the mediator variable in a (multivariate
response) mediator-model. If missing, mediation() tries to find the
treatment variable automatically, however, this may fail.
Vector of scalars between 0 and 1, indicating the mass within the credible interval that is to be estimated.
The typical value that will represent the Bayesian point estimate.
By default, the posterior median is returned. See typical_value
for possible values for this argument.
A data frame with direct, indirect, mediator and total effect of a multivariate-response mediation-model, as well as the proportion mediated. The effect sizes are mean values of the posterior samples.
mediation() returns a data frame with information on the
direct effect (mean value of posterior samples from treatment
of the outcome model), mediator effect (mean value of posterior
samples from mediator of the outcome model), indirect effect
(mean value of the multiplication of the posterior samples from
mediator of the outcome model and the posterior samples from
treatment of the mediation model) and the total effect (mean
value of sums of posterior samples used for the direct and indirect
effect). The proportion mediated is the indirect effect divided
by the total effect.
For all values, the 90% HDIs are calculated by default. Use prob
to calculate a different interval.
The arguments treatment and mediator do not necessarily
need to be specified. If missing, mediation() tries to find the
treatment and mediator variable automatically. If this does not work,
specify these variables.