Robust variance estimation in linear regression

Abstract

The standard technique for estimating the variance of a linear regression coefficient is unbiased when the random errors of the observational units are independent and identically distributed. When the unit variances are not all equal, however, as is often the case in practice, this method can be biased. An unbiased variance estimator given uncorrelated, but not necessarily homoscedastic, unit errors is introduced here and compared to the conventional technique using real data.