Question

I can extract the p-values for my slope & intercept from an ols object this way:

library(rms)
m1 <- ols(wt ~ cyl, data= mtcars, x= TRUE, y= TRUE)
coef(summary.lm(m1))

But when I try the same thing with a robcov object, summary.lm gives me the p-values from the original model (m1), not the robcov model:

m2 <- robcov(m1)
m2
coef(summary.lm(m2))

I think this must be related to the Warning from the robcov help page,

Warnings

Adjusted ols fits do not have the corrected standard errors printed
with print.ols. Use sqrt(diag(adjfit$var)) to get this, where adjfit
is the result of robcov.

but I’m not sure how.

Is there a way to extract the p-values from a robcov object? (I’m really only interested in the one for the slope, if that makes a difference…)

Answer 1

Hacking through print.ols and prModFit, I came up with this.

errordf <- m2$df.residual
beta <- m2$coefficients
se <- sqrt(diag(m2$var))
Z <- beta/se
P <- 2 * (1 - pt(abs(Z), errordf))

Change m2 to another robcov model.

Try it for yourself by comparing the results of P to print(m2)