fixed_effects: Effects of covariates on outcome in baggr models

In baggr: Bayesian Aggregate Treatment Effects

Effects of covariates on outcome in baggr models

Description

Effects of covariates on outcome in baggr models

Usage

fixed_effects(bg, summary = FALSE, transform = NULL, interval = 0.95)

Arguments

bg	a baggr() model
summary	logical; if TRUE returns summary statistic instead of all MCMC samples
transform	a transformation (R function) to apply to the result; (this is commonly used when calling from other plotting or printing functions)
interval	uncertainty interval width (numeric between 0 and 1), if summary=TRUE

Value

A matrix: columns are covariate coefficients and rows are draws from the posterior distribution. Number of rows depends on iterations in the MCMC (i.e. x in baggr(..., iter = x')

See Also

treatment_effect for overall treatment effect across groups, group_effects for effects within each group, effect_draw and effect_plot for predicted treatment effect in new group (which you can condition on fixed effects using new data argument)

baggr documentation built on June 16, 2026, 9:06 a.m.