I've used an ordinary least square linear regression model in R that looks something like this:
ols <- lm(DV ~ IV1 + IV2)
When I type this:
summary(ols)
I get a table showing Estimate, Std Error, t value and P(>|t|) for each coefficient. I also get the residual standard error, multiple r-square, adjusted r-square, f-statistic, and p-value for the model.
And I've used a robust linear regression model that looks something like this:
roblm <- rlm(DV ~ IV1 + IV2)
When I type this:
summary(roblm)
I get a table showing Value, Std Error, and t value for each coefficient. But I don't get a p-value for each coefficient. Similarly, I get the residual standard error for the model, but I don't get multiple r-square, adjusted r-square, f-statistic, and p-value for the model.
Why aren't these additional statistics provided for the robust linear regression model? Do they not make sense in the context of this model? If these statistics do make sense, how would I go about getting them?
library(robustbase)
and look at the newer robust methods there, which come with more extensive summary methods. $\endgroup$