Prediction-interval procedures and (fixed-effects) confidence-interval procedures for mixed linear models (Q3793561)

varianwhich employs a modification of the so-called least-failures sampling rule is proposed, and is shown to possess many desirable properties among a restricted class of Bernoulli subset selection procedures. Within this class, it is optimal for minimizing the number of observations taken from populations excluded from consideration following a subset selection experiment, and asymptotically optimal for minimizing the expected total number of observations required. In addition, it can result in substantial savings in the expected total number of observations required as compared to a single-stage procedure, thus it may be desirable to a practitioner if sampling is costly or the sample size is limited