bayesMargCompareF {bayesMeanScale}

Comparison of Bayesian marginal effects

Description

Tests the differences between all marginal effects in the "bayes_mean_scale_marg" object that is passed to it. This is particularly useful for testing non-linear interaction effects.

Usage

bayesMargCompareF(marg_list,
                  ci           = 0.95,
                  hdi_interval = TRUE,
                  centrality   = 'mean',
                  digits       = 4)

Arguments

marg_list

An object of class "bayes_mean_scale_marg."

ci

The level of the credible interval.

hdi_interval

If TRUE, the default, computes the highest density credible interval. If FALSE, computes the equal-tailed interval.

centrality

Centrality measure for the posterior distribution. Options are "mean" or "median".

digits

The number of digits to report in the summary table.

Details

All possible differences of marginal effects contained in the "bayes_mean_scale_marg" object are computed.

Value

A list of class "bayes_mean_scale_marg_compare" with the following components:

diffTable

summary table of the differences of the marginal effects

diffDraws

posterior draws of the differences of the marginal effects

Author(s)

David Dalenberg

References

Mize, Trenton D. 2019. "Best Practices for Estimating, Interpreting, and Presenting Non-linear Interaction Effects." Sociological Science 6: 81-117.

Examples

## Logit model ##

if(require(rstanarm)){

m1 <- stan_glm(switch ~ dist + educ + arsenic + assoc, 
               data    = rstanarm::wells, 
               family  = binomial, 
               refresh = 0,
               iter    = 500)

m1Marg <- bayesMargEffF(m1, 
                        marginal_effect = 'arsenic', 
                        start_value     = 2.2, 
                        end_value       = .82, 
                        at              = list(educ=c(0, 5)),
                        n_draws         = 500)

bayesMargCompareF(m1Marg)

}