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Bias Error in Yield Functions as Influenced by Treatment Design and Postulated Model¹

ABSTRACT

Bias error occurs when the fitted or postulated model is not equal to the true functional relationship between the dependent variable and the independent variable(s). The concept of bias error is developed and the effect of various factors on magnitude of the bias error studied. The factors included in an empirical study are spacing and number of fertilizer levels and selection of the postulated model. The choice of a postulated model, a factor not under the control of the experimenter during the planning stages of an experiment, shows the largest influence on bias error. The selection of the postulated model is discussed and suggestions for the control of bias and variance error in response surface experimentation are given.

¹ Joint contribution of the Department of Statistics, University of Kentucky, Lexington, and the International Maize and Wheat Improvement Center, Londres 40, Mexico 6, D.F.

² Professor of Statistics and Agronomy and Soil Scientist, respectively.

Received for publication May 23, 1968. Accepted for publication October 28, 1968.