His email address is ments previously thought to be completely randomized experiments also exhibit split-plot structure. Carlson Professor and Chair of the Operations and Management Science Department at the Carlson School of Management of the University of Minnesota. Jones is Director of Research and Development for the JMP Division of SAS Institute, Inc. (2004)) has demonstrated that many experi- Dr. Recent work, most notably by Lucas and his coworkers (Anbari and Lucas (1994), Ganju and Lucas (1997, 1999, 2005), Ju and Lucas (2002), Webb et al. This is frequently the case when hard-to-change factors exist and economic constraints preclude the use of complete randomization. It is also well known that many industrial experiments are fielded as split-plot experiments and yet erroneously analyzed as if they were completely randomized designs. Split-Plot experiments were invented by Fisher (1925) and their importance in industrial experimentation has been long recognized (Yates (1936)). (2005) in their well-known text on the design of experiments.
THIS provocative remark has been attributed to the famous industrial statistician, Cuthbert Daniel, by Box et al. Introduction All industrial experiments are split-plot experiments.
Key Words: Block Designs Completely Randomized Designs Factorial Designs Fractional Factorial Designs Optimal Designs Random-Effects Model Random-Run-Order Designs Response Surface Designs Robust Parameter Designs. In this paper, we review recent developments and provide guidelines for the use of split-plot designs in industrial applications.
Unfortunately, the value of these designs for industrial experimentation has not been fully appreciated. NACHTSHEIM Carlson School of Management, University of Minnesota, Minneapolis, MN 55455 The past decade has seen rapid advances in the development of new methods for the design and analysis of split-plot experiments. Split-Plot Designs: What, Why, and How BRADLEY JONES SAS Institute, Cary, NC 27513 CHRISTOPHER J.
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