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References (26)
-
H. Monod, J. Azaïs, R. Bailey (1996)
VALID RANDOMISATION FOR THE FIRST‐DIFFERENCE ANALYSISAustralian & New Zealand Journal of Statistics, 38
-
E. Williams (1986)
NEIGHBOUR ANALYSIS OF UNIFORMITY DATAAustralian & New Zealand Journal of Statistics, 28
-
Nelder Nelder (1965a)
The analysis of randomized experiments with orthogonal block structure. I. Block structure and the null analysis of varianceProc. R. Soc. Series A, 283
-
David Cox (2009)
Randomization in the Design of ExperimentsInternational Statistical Review, 77
-
Kempthorne Kempthorne (1977)
Why randomize?J. Stat. Plan. Inference, 1
-
Nelder Nelder (1965b)
The analysis of randomized experiments with orthogonal block structure. II. Treatment structure and the general analysis of varianceProc. R. Soc. Series A, 283
-
Williams Williams, Luckett Luckett (1988)
The use of uniformity data in the design and analysis of cotton and barley variety trialsAust. J. Agric. Res., 39
-
H. Piepho, C. Richter, J. Spilke, K. Hartung, A. Kunick, H. Thöle (2011)
Statistical aspects of on-farm experimentationCrop & Pasture Science, 62
-
W. Leiser, H. Rattunde, H. Piepho, H. Parzies (2012)
Getting the Most Out of Sorghum Low-Input Field Trials in West Africa Using Spatial AdjustmentJournal of Agronomy and Crop Science, 198
-
Jonathan Mühleisen, J. Reif, H. Maurer, J. Möhring, H. Piepho (2013)
Visual Scorings of Drought Stress Intensity as Covariates for Improved Variety Trial AnalysisJournal of Agronomy and Crop Science, 199
-
R. Edmondson (2005)
Past developments and future opportunities in the design and analysis of crop experimentsThe Journal of Agricultural Science, 143
-
E. Williams, D. Luckett (1988)
The use of uniformity data in the design and analysis of cotton and barley variety trialsCrop & Pasture Science, 39
-
C. Brien, C. Demétrio (2009)
Formulating mixed models for experiments, including longitudinal experimentsJournal of Agricultural, Biological, and Environmental Statistics, 14
-
H. Smith (1938)
An empirical law describing heterogeneity in the yields of agricultural cropsThe Journal of Agricultural Science, 28
-
H. Piepho, A. Büchse, C. Richter (2004)
A Mixed Modelling Approach for Randomized Experiments with Repeated MeasuresJournal of Agronomy and Crop Science, 190
-
R. Bailey, J. Azaïs, H. Monod (1995)
Are neighbour methods preferable to analysis of variance for completely systematic designs? ‘Silly designs are silly!’Biometrika, 82
-
E. Williams, J. John, D. Whitaker (2006)
Construction of Resolvable Spatial Row–Column DesignsBiometrics, 62
-
Grundy Grundy, Healy Healy (1950)
Restricted randomization and quasi‐Latin squaresJ. R. Stat. Soc. Series B, 12
-
A. Gilmour, B. Cullis, A. Verbyla (1997)
Accounting for natural and extraneous variation in the analysis of field experimentsJournal of Agricultural Biological and Environmental Statistics, 2
-
C. Richter, B. Kroschewski (2012)
Geostatistical Models in Agricultural Field Experiments: Investigations Based on Uniformity TrialsAgronomy Journal, 104
-
E. Pitman (1938)
SIGNIFICANCE TESTS WHICH MAY BE APPLIED TO SAMPLES FROM ANY POPULATIONS III. THE ANALYSIS OF VARIANCE TESTBiometrika, 29
-
T. Loughin, M. Roediger, G. Milliken, J. Schmidt (2007)
On the analysis of long‐term experimentsJournal of the Royal Statistical Society: Series A (Statistics in Society), 170
-
H. Piepho, E. Williams (2010)
Linear variance models for plant breeding trialsPlant Breeding, 129
-
T. Haase, C. Schüler, H. Piepho, H. Thöni, J. Heß (2007)
The Effect of Preceding Crop and Pre‐Sprouting on Crop Growth, N Use and Tuber Yield of Maincrop Potatoes for Processing Under Conditions of N StressJournal of Agronomy and Crop Science, 193
-
Edmondson Edmondson (1993)
Systematic row‐and‐column designs balanced for low order polynomial interactions between rows and columnsJ. R. Stat. Soc. Series B, 55
-
M. Kenward, J. Roger (2009)
An improved approximation to the precision of fixed effects from restricted maximum likelihoodComput. Stat. Data Anal., 53
- Publisher
- Wiley
- Copyright
- Copyright © 2013 Blackwell Verlag GmbH
- ISSN
- 0931-2250
- eISSN
- 1439-037X
- DOI
- 10.1111/jac.12026
- Publisher site
- See Article on Publisher Site
Abstract
This study illustrates the importance of randomization using two hypothetical field trials, one with a marked systematic trend and the other with a more erratic spatial pattern. The insights from these two examples are reinforced by analysis of a uniformity trial and a small simulation study. Results illustrate that both model‐based spatial analysis and randomization‐based analysis assuming independent errors are valid with full randomization but may be invalidated when randomization is lacking. It is concluded that randomization provides protection against different forms of spatial trend. The examples given in the study serve as a general reminder that agricultural experiments should be randomized whenever possible.
Journal
Journal of Agronomy and Crop Science – Wiley
Published: Oct 1, 2013