I would expect that for simple hypothesis of the form model_parameter < 0
hypothesis
would return CIs mirroring the model summary. However, there tends to be a small difference… am I misunderstanding something about how hypothesis
or summary
works?
An example:
library(tidyverse)
library(brms)
fit <- brm(y ~ x, data = data.frame(x = rnorm(30)) %>% mutate(y = rnorm(30, x)))
summary(fit)
# Population-Level Effects:
# Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
# Intercept -0.13 0.22 -0.55 0.30 1.00 3647 2503
# x 0.91 0.21 0.49 1.33 1.00 3593 2549
hypothesis(fit, "x < 0")
# Hypothesis Estimate Est.Error CI.Lower CI.Upper Evid.Ratio Post.Prob Star
# 1 (x) < 0 0.91 0.21 0.56 1.26 0 0