Split-plot designs are frequently needed in practice because of practical limitations and issues related to cost. This imposes extra challenges on the experimenter, both when designing the experiment and when analysing the data, in particular for non-replicated cases. This paper is an overview and discussion of some of the most important methods for analysing split-plot data. The focus is on estimation, testing and model validation. Two examples from an industrial context are given to illustrate the most important techniques. Copyright (c) 2006 John Wiley & Sons, Ltd.
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Univ New England, Dept Math Sci, 11 Hills Beach Rd, Biddeford, ME 04005 USAUniv New England, Dept Math Sci, 11 Hills Beach Rd, Biddeford, ME 04005 USA
Koh, Woon Yuen
Eskridge, Kent M.
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Univ Nebraska, Dept Statistics, Lincoln, NE 68583 USAUniv New England, Dept Math Sci, 11 Hills Beach Rd, Biddeford, ME 04005 USA
Eskridge, Kent M.
Hanna, Milford A.
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Univ Nebraska, Dept Biol Syst Engn, Lincoln, NE 68583 USAUniv New England, Dept Math Sci, 11 Hills Beach Rd, Biddeford, ME 04005 USA
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SHEFFIELD CITY POLYTECH,DEPT MATH STAT & OPERAT RES,SHEFFIELD S1 1WB,S YORKSHIRE,ENGLANDSHEFFIELD CITY POLYTECH,DEPT MATH STAT & OPERAT RES,SHEFFIELD S1 1WB,S YORKSHIRE,ENGLAND
KANJI, GK
LIU, CK
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SHEFFIELD CITY POLYTECH,DEPT MATH STAT & OPERAT RES,SHEFFIELD S1 1WB,S YORKSHIRE,ENGLANDSHEFFIELD CITY POLYTECH,DEPT MATH STAT & OPERAT RES,SHEFFIELD S1 1WB,S YORKSHIRE,ENGLAND