使用Rstanarm计算二项式Logit中的边际效应的可信区间

Question

In this method for calculating marginal effects for a binomial logit using rstanarm, https://stackoverflow.com/a/45042387/9264004

nd <- md
nd$x1 <- 0
p0 <- posterior_linpred(glm1, newdata = nd, transform = TRUE)
nd$x1 <- 1
p1 <- posterior_linpred(glm1, newdata = nd, transform = TRUE)
ME <- p1 - p0
AME <- rowMeans(ME)

Can intervals for the marginal effects be calculated by taking quantiles, like this:

QME <- quantile(AME, c(.025,.25,.5,.75,.975))

or is there a more correct way to calculate a standard error for the effect?

Answer 1

If you are interested in the posterior standard deviation of the average (over the data) "marginal" effect of changing x1 from 0 to 1, then it would be sd(ME) or possibly mad(ME) . But if you want quantiles, then call quantile .