Imputation methods for missing response values in the three parts of a central composite design with two factors

Abstract

This study compares four methods (Mean, Part-mean, Regression, and K-nearest neighbor (KNN)) for imputing the missing response values in a CCD. Four test functions are used to perform all possible cases of a single missing response in a CCD with two factors. The performance was measured by using the mean-squared error and correlation coefficient of the three parts of the CCD (factorial, center, or axial) by comparing the imputed and actual values. The study results show that the missing response value's influence of the affected part of the CCD (factorial, center, axial) could not be neglected, and the Regression imputation method was superior to the other three for an imputed value in the factorial or axial parts of the CCD. Furthermore, for missing values in the center part, the results show that the Part-mean imputation method was equally as good as the complex imputation methods of Regression and KNN.