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Optimal versus orthogonal and equivalent‐estimation design of blocked and split‐plot experiments
Author(s) -
Goos Peter
Publication year - 2006
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.2006.00333.x
Subject(s) - equivalence (formal languages) , plot (graphics) , split plot , restricted randomization , mathematics , design of experiments , mathematical optimization , ordinary least squares , optimal design , least squares function approximation , algorithm , computer science , statistics , discrete mathematics , randomized block design , medicine , surgery , randomization , estimator , randomized controlled trial
This article provides an overview of the recent literature on the design of blocked and split‐plot experiments with quantitative experimental variables. A detailed literature study introduces the ongoing debate between an optimal design approach to constructing blocked and split‐plot designs and approaches where the equivalence of ordinary least squares and generalized least squares estimates are envisaged. Examples where the competing design strategies lead to totally different designs are given, as well as examples in which the optimal experimental designs are orthogonally blocked or equivalent‐estimation split‐plot designs.