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Accurate Tolerance Limits for a Two-Way Nested Random Effects Model

Abstract:

We consider in this article a method of constructing accurate $\beta$-content tolerance limits for a two-way nested model with normal random effects. The procedure is derived by conditioning on an estimator of the unknown expected mean square ratio as proposed in Chen and Harris (2006). Simulation studies indicate that the present procedure is less conservative than current existing methods and gives more accurate coverage rates. Statistical tables needed to implement the procedure are included.