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On a mixed model analysis of multi-environment variety trials: a reconsideration of the one-stage and the two-stage models and analyses

Author

Listed:
  • T. Caliński

    (Poznań University of Life Sciences)

  • S. Czajka

    (Poznań University of Life Sciences)

  • Z. Kaczmarek

    (Polish Academy of Sciences)

  • P. Krajewski

    (Polish Academy of Sciences)

  • W. Pilarczyk

    (Poznań University of Life Sciences)

  • I. Siatkowski

    (Poznań University of Life Sciences)

  • M. Siatkowski

    (Poznań University of Life Sciences)

Abstract

Of interest is the analysis of results of a series of experiments conducted at several environments with the same set of plant varieties (called multi-environment variety trials). The most common practice is first to analyze individual trials and then to perform a kind of “synthesis” of the results obtained. This is considered as a two-stage approach to the analysis of the trial data. More recently a combined analysis of the raw plot data from all trials taken simultaneously has been advocated, as a one-stage approach to the analysis. The purpose of this article is to reconsider these two approaches with regard to the underlying models and the analyses based on them. The indicated differences between them are illustrated by a thorough analysis of a set of data from a series of trials with rye varieties. The required computations have been accomplished with the use of R.

Suggested Citation

  • T. Caliński & S. Czajka & Z. Kaczmarek & P. Krajewski & W. Pilarczyk & I. Siatkowski & M. Siatkowski, 2017. "On a mixed model analysis of multi-environment variety trials: a reconsideration of the one-stage and the two-stage models and analyses," Statistical Papers, Springer, vol. 58(2), pages 433-465, June.
    • Handle: RePEc:spr:stpapr:v:58:y:2017:i:2:d:10.1007_s00362-015-0706-y
    DOI: 10.1007/s00362-015-0706-y
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    References listed on IDEAS

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    1. T. Caliński & S. Czajka & Z. Kaczmarek & P. Krajewski & W. Pilarczyk, 2005. "Analyzing Multi-environment Variety Trials Using Randomization-Derived Mixed Models," Biometrics, The International Biometric Society, vol. 61(2), pages 448-455, June.
    2. Rao, C. Radhakrishna, 1973. "Representations of best linear unbiased estimators in the Gauss-Markoff model with a singular dispersion matrix," Journal of Multivariate Analysis, Elsevier, vol. 3(3), pages 276-292, September.
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