On Lower Tolerance Limits With Accurate Coverage Probabilities for the Normal Random Effects Model

Abstract

A method for constructing accurate lower tolerance limits for the balanced one-way normal random-effects model is derived by conditioning on an estimator of the unknown expected mean square ratio. Simulation studies indicate that the present procedure is less conservative than that of several existing methods and gives more accurate coverage rates and smaller standard deviations. Numerical examples are given to illustrate the use of the new procedure. Tables needed to implement the procedure are also included.