00000cab a22000003a 4500 UP-99796217610203654 Buklod 20231008000558.0 a grb 001 u| ta 120215s xx d | ||r ||||| || DENG eng Macharia, Harrison D-optimal and d-efficient equivalent-estimation second-order split-plot designs. pp. 358 Industrial experiments often involve factors that are hard to change or costly to manipulate and thus make it undesirable to use a complete randomization. In such cases, the split plot design structure is a cost efficient alternative that reduces the number of independent settings of the hard to change factors. In general, model estimation for split plot designs requires the use of generalized least squares (GLS). However, for some split plot designs (including not only classical agricultural split plot designs, but also some second order split plot response surface designs), ordinary least squares (OLS) estimates are equivalent to GLS estimates. These designs are called equivalent estimation designs and offer the advantage that estimation of the factor effects does not require estimation of the variance components in the split plot model. As an alternative to these equivalent estimation designs, one can use D-optimal designs that guarantee efficient estimation of the fixed effects of the statistical model that is appropriate given the split plot structure. We explore the relationship between equivalent-estimation and D-optimal split plot designs for a second order response surface model and propose an algorithm for generating D-efficient equivalent estimation split plot designs. This approach allows for a flexible choice of the number of hard to change factors, the number of easy to change factors, the number of whole plots, and the total sample size. Coordinate-Exchange Algorithm. D-optimality. Equivalent estimation. Generalized least squares. Ordinary least squares. Split plot design. Journal of Quality Technology 42, 4 (2010). FO UPD DENG Article