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Abstract
Journal of Official Statistics, Vol.18, No.2, 2002. pp. 291303

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Multiple-Objective Optimal Designs for the Hierarchical Linear Model

Abstract:
Optimal designs are usually constructed under a single optimality criterion. Such designs are not very realistic in practice because a researcher seldom has just one objective in mind when designing an experiment. This problem can be overcome by multiple-objective designs. Here, we extend previous work and construct multiple-objective designs for situations where the data are correlated using a hierarchical linear model. We present a graphical method for constructing multiple-objective designs and investigate their robustness properties.

Keywords:
Hierarchical data; sample size; optimality criteria; variance components.

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