Closed acoppock closed 1 year ago
library(estimatr) dat <- data.frame( Y = rnorm(100), Z = rbinom(100, 1, 0.5) ) lm_robust(Y ~ Z, data = dat) lm_robust(Y ~ Z, alpha = 0.10, data = dat)
returns:
> lm_robust(Y ~ Z, data = dat) Estimate Std. Error t value Pr(>|t|) CI Lower CI Upper DF (Intercept) 0.2332325 0.1353415 1.7232889 0.08799008 -0.0353483 0.5018132 98 Z -0.1578283 0.1921291 -0.8214704 0.41337238 -0.5391022 0.2234455 98 > lm_robust(Y ~ Z, alpha = 0.10, data = dat) Estimate Std. Error t value Pr(>|t|) CI Lower CI Upper DF (Intercept) 0.2332325 0.1353415 1.7232889 0.08799008 0.008491007 0.4579739 98 Z -0.1578283 0.1921291 -0.8214704 0.41337238 -0.476868457 0.1612118 98
p-values should be different
Shouldn't it just affect the width of the CIs? Not the p?
lmao im sure Neal is right but I don't trust past luke at all so instead of closing this I'm gonna ask Alex to follow-up.
returns:
p-values should be different