A SOLUTION TO THE EFFECT OF SAMPLE-SIZE ON OUTLIER ELIMINATION

Results from a Monte Carlo study demonstrate how a non-recursive, a si mple recursive, a modified recursive, and a hybrid outlier elimination procedure are influenced by population skew and sample size. All the procedures are based on computing a mean and a standard deviation from a sample in order to determine whether an observation is an outlier. Miller (1991) showed that the estimated mean produced by the simple no n-recursive procedure can be affected by sample size and that this eff ect can produce a bias in certain kinds of experiments. We extended th is result to the other three procedures. We also create two new proced ures in which the criterion used to identify outliers is adjusted as a function of sample size so as to produce results that are unaffected by sample size.