Subset selection for an almost best treatment

A generalized goal using subset selection is discussed for the location parameter case. This goal is to select a non-empty subset from a set of k (k 2) treatments that contains at least one -best treatment with confidence level P*. For a set of treatments an -best treatment is defined as a treatment with location parameter on a distance less than or equal to ( o) from the best treatment, where best is defined as largest value of the location parameter. The efficiency of subset selection of an -best treatment relative to subset selection of the best treatment is investigated and is computed for some values of k and the confidence level for the Normal case as well as for the Logistic case.