A mixed model analysis of variance for multi-environment variety trials

DOI10.1007/s00362-009-0249-1zbMath1247.62287OpenAlexW2066518468MaRDI QIDQ451319

Tadeusz Caliński, Wiesław Pilarczyk, Stanisław Czajka, Paweł Krajewski, Zygmunt Kaczmarek

Publication date: 23 September 2012

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-009-0249-1

zbMATH Keywords

estimationhypothesis testingmixed effects modelseries of experimentsvariety by environment interactions

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Statistical block designs (62K10) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (3)

On a mixed model analysis of multi-environment variety trials: a reconsideration of the one-stage and the two-stage models and analyses ⋮ The use of a reference variety for comparisons in incomplete series of crop variety trials ⋮ A conversation with Professor Tadeusz Caliński

Cites Work

• Balance in designed experiments with orthogonal block structure
• Representations of best linear unbiased estimators in the Gauss-Markoff model with a singular dispersion matrix
• Analyzing the genotype-by-environment interactions under a randomization-derived mixed model
• Analyzing Variety by Environment Data Using Multiplicative Mixed Models and Adjustments for Spatial Field Trend
• ITERATIVE ANALYSIS OF GENERALIZED LATTICE DESIGNS
• A new class of resolvable incomplete block designs
• Applications: The Analysis of Crop Variety Evaluation Data in Australia
• REML Estimation of Multiplicative Effects in Multienvironment Variety Trails
• Estimation of variance and covariance components—MINQUE theory
• Estimation of Variance and Covariance Components in Linear Models
• Analyzing Multi‐environment Variety Trials Using Randomization‐Derived Mixed Models
• The analysis of randomized experiments with orthogonal block structure. I. Block structure and the null analysis of variance
• The interpretation of negative components of variance
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