The Effect of Trimming and Normality Assumptions on the Efficiency of the O-BLUE Estimators

The seriousness of trimming samples, and considering the trimmed samples as if they are complete samples of the retained size, from a normal distribution is explored for the parameters of the simple linear regression model. The exact efficiencies of the O-BLUE estimators of the parameters under these conditions are investigated relative to the O-BLUE estimators based upon the trimmed samples from the actual distribution G. Five symmetric distributions are considered. It is found that the overall loss in relative efficiency is quite substantial especially when the true distribution has heavier tails than the normal distribution, and in particular for larger amounts of trimming.