(Received July 1, 1991; revised October 21, 1991)
Abstract. When an empirical model is fitted to data, bias can arise from terms that have not been incorporated, and this can have an important effect on the choice of an experimental design. Here, the biases are treated as random, and the consequences of this action are explored for the fitting of models of first and second order.
Key words and phrases: Bias error, experimental design, response surface, variance error.
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