Efficient experimental designs when most treatments are unreplicated

Martin, R. J., Chauhan, N., Eccleston, J. A. and Chan, B. S. P. (2006) Efficient experimental designs when most treatments are unreplicated. Linear Algebra and its Applications, 417 1: 163-182. doi:10.1016/j.laa.2006.02.009


Author Martin, R. J.
Chauhan, N.
Eccleston, J. A.
Chan, B. S. P.
Title Efficient experimental designs when most treatments are unreplicated
Journal name Linear Algebra and its Applications   Check publisher's open access policy
ISSN 0024-3795
1873-1856
Publication date 2006-08-01
Sub-type Article (original research)
DOI 10.1016/j.laa.2006.02.009
Volume 417
Issue 1
Start page 163
End page 182
Total pages 20
Editor Ludwig Elsner
Augustyn Markiewicz
Tomasz Szulc
Place of publication Philadelphia, PA, U.S.A.
Publisher Elsevier
Collection year 2006
Language eng
Subject C1
230203 Statistical Theory
780100 Non-oriented Research
Abstract In early generation variety trials, large numbers of new breeders' lines (varieties) may be compared, with each having little seed available. A so-called unreplicated trial has each new variety on just one plot at a site, but includes several replicated control varieties, making up around 10% and 20% of the trial. The aim of the trial is to choose some (usually around one third) good performing new varieties to go on for further testing, rather than precise estimation of their mean yields. Now that spatial analyses of data from field experiments are becoming more common, there is interest in an efficient layout of an experiment given a proposed spatial analysis and an efficiency criterion. Common optimal design criteria values depend on the usual C-matrix, which is very large, and hence it is time consuming to calculate its inverse. Since most varieties are unreplicated, the variety incidence matrix has a simple form, and some matrix manipulations can dramatically reduce the computation needed. However, there are many designs to compare, and numerical optimisation lacks insight into good design features. Some possible design criteria are discussed, and approximations to their values considered. These allow the features of efficient layouts under spatial dependence to be given and compared. (c) 2006 Elsevier Inc. All rights reserved.
Keyword Dependent Observations
Early Generation Variety Trials
Generalized Least-squares
Optimality Criteria
Optimal Design
Generation Variety Trials
Crop Varieties
Information
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 3 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 15 Aug 2007, 20:27:58 EST