A Selection Procedure Using a Screening Variate

Richard Madsen

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Advanced Statistical Process Monitoring Probability and Statistical Research Optimal Experimental Design Methods

Abstract

Consider N objects on which two correlated measurements X and Y can be made and where the measurement of X is easier or less expensive to make than the one of Y. Suppose that the probability that the Y measurement meets a certain specification is γ. We present a method, which uses the conditional probabilities that Y will meet the specification given the observed value of the x's, for choosing a maximal subset of m out of the N objects, based on the observed X measurements, so that there is a high probability that a large proportion (Π ≥ γ) of the selected subset will meet the desired specification. The procedure is useful for helping to meet a guaranteed proportion of satisfactory items. It compares favorably with one suggested by Owen, Li, and Chou (1981).

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References

1939The relationship of validity coefficients to the practical effectiveness of tests in selection: discussion and tables.1981Tables for Normal Tolerance Limits, Sampling Plans and Screening 1975Tables Using One or Two Screening Variables to Increase Acceptable Product Under One-Sided Specifications 1977Screening Based on Normal Variables 1981Prediction Intervals for Screening Using a Measured Correlated Variate 1979Two-Sided Screening Procedures in the Bivariate Case

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