Forkman, Johannes and Piepho, Hans-Peter
(2013).
Performance of empirical BLUP and Bayesian prediction in small
randomized complete block experiments.
Journal of agricultural science. 151
:3
, 381-395
[Research article]
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Official URL: http://dx.doi.org/10.1017/S0021859612000445
Abstract
The model for analysis of randomized complete block (RCB) experiments usually includes two factors: block and
treatment. If treatment is modelled as fixed, best linear unbiased estimation (BLUE) is used, and treatment means
estimate expected means. If treatment is modelled as random, best linear unbiased prediction (BLUP) shrinks the
treatment means towards the overall mean, which results in smaller root-mean-square error (RMSE) in prediction
of means. This theoretical result holds provided the variance components are known, but in practice the variance
components are estimated. BLUP using estimated variance components is called empirical best linear unbiased
prediction (EBLUP). In small experiments, estimates can be unreliable and the usefulness of EBLUP is uncertain.
The present paper investigates, through simulation, the performance of EBLUP in small RCB experiments with
normally as well as non-normally distributed random effects. The methods of Satterthwaite (1946) and of Kenward
& Roger (1997, 2009), as implemented in the SAS System, were studied. Performance was measured by RMSE, in
prediction of means, and coverage of prediction intervals. In addition, a Bayesian approach was used for
prediction of treatment differences and computation of credible intervals. EBLUP performed better than BLUE with
regard to RMSE, also when the number of treatments was small and when the treatment effects were non-normally
distributed. The methods of Satterthwaite and of Kenward & Roger usually produced approximately correct
coverage of prediction intervals. The Bayesian method gave the smallest RMSE and usually more accurate
coverage of intervals than the other methods.
Authors/Creators: | Forkman, Johannes and Piepho, Hans-Peter | ||||||
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Title: | Performance of empirical BLUP and Bayesian prediction in small randomized complete block experiments | ||||||
Series Name/Journal: | Journal of agricultural science | ||||||
Year of publishing : | June 2013 | ||||||
Volume: | 151 | ||||||
Number: | 3 | ||||||
Page range: | 381-395 | ||||||
Publisher: | Cambridge University Press | ||||||
ISSN: | 0021-8596 | ||||||
Language: | English | ||||||
Publication Type: | Research article | ||||||
Refereed: | Yes | ||||||
Article category: | Scientific peer reviewed | ||||||
Version: | Published version | ||||||
Full Text Status: | Public | ||||||
Subjects: | (A) Swedish standard research categories 2011 > 1 Natural sciences > 101 Mathematics > 10106 Probability Theory and Statistics | ||||||
Keywords: | Best linear unbiased prediction, Randomized complete block experiment | ||||||
URN:NBN: | urn:nbn:se:slu:epsilon-e-1939 | ||||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-1939 | ||||||
Additional ID: |
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ID Code: | 11240 | ||||||
Faculty: | NJ - Fakulteten för naturresurser och jordbruksvetenskap | ||||||
Department: | (NL, NJ) > Dept. of Crop Production Ecology | ||||||
Deposited By: | Johannes Forkman | ||||||
Deposited On: | 02 Jun 2014 09:46 | ||||||
Metadata Last Modified: | 24 Jan 2015 01:50 |
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