I am running a linear regression (just a single IV) and have selected the robust error option (
vce robust) in Stata due to heteroscedasticity (and because it is sometimes recommended to do so anyway). However, try as I might, I cannot find any advice on whether I should be testing for normality after I have selected this robust option or whether running the robust option negates the need to do so. Any help on whether normality should be tested with this option checked would be greatly appreciated.
BASED ON ANSWERS: My main focus is on understanding the regression model, so I will be looking at the (slope) coefficient and its 95% CI as well as statistical significance (I have a continuous IV). In another linear regression I had hoped to make predictions (with CI and, hopefully, PI) also. I was OK with checking the assumptions of a regression analysis until I reached the option to use robust standard errors. From the answers received am I correct in saying that asymptotic normality is needed, but not readily/easily tested for (and is rarely tested in practice)? So I could run the regression with robust errors and not test for normality. I assume that other assumptions (e.g., unusual points) still hold. I checked Stata and it does seem that it predicts when robust errors are used. Is it correct to use these predictions?