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In robust parameter design, a compound noise experiment has been frequently used for reducing the number of experimental runs compared to a product array experiment. However, the results obtained by the compound noise experiment and the product array experiment are often much different. This paper derives an expression of the correlation coefficient of response variances in the compound noise and the product array experiments, which gives an explanation of that difference. [ABSTRACT FROM PUBLISHER]

Robust parameter design has been widely used to improve the quality of products and processes. Although a product array, in which an orthogonal array for control factors is crossed with an orthogonal array for noise factors, is commonly used for parameter design experiments, this may lead to an unacceptably large number of experimental runs. The compound noise strategy proposed by Taguchi [30] can be used to reduce the number of experimental runs. In this strategy, a compound noise factor is formed based on the directionality of the effects of noise factors. However, the directionality is usually unknown in practice. Recently, Singhet al.[28] proposed a random compound noise strategy, in which a compound noise factor is formed by randomly selecting a setting of the levels of noise factors. The present paper evaluates the random compound noise strategy in terms of the precision of the estimators of the response mean and the response variance. In addition, the variances of the estimators in the random compound noise strategy are compared with those in then-replication design. The random compound noise strategy is shown to have smaller variances of the estimators than the 2-replication design, especially when the control-by-noise-interactions are strong. [ABSTRACT FROM AUTHOR]

Fellegi's (1974) improved method for estimating the interviewer component of correlated response variance is extended to I groups of k interviewer assignments for general multistage survey designs. Using a linear models approach suggestive of Hartley and Rao's (1978), the independence of the two estimators of interviewer variance is established and the forms of the variances of the estimators are derived. Then using 1980 census data to compute terms in the estimator variances, (a) the optimal design of interviewer variance studies is considered, (b) the improvement of the composite estimator is demonstrated, and (c) some principles of efficient study design are developed. [ABSTRACT FROM AUTHOR]