Claim · model-written summary
The analysis allowed unbalanced data and heterogeneous variances.
- Outcome
- working with unbalanced data and the incorporation of heterogeneity of variancese0
- Comparator
- unbalanced datae0
Zea maysNot reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentSettingDirectionValueQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the flexibility of the analysis facilitated working with unbalanced data and the incorporation of heterogeneity of variances”
e1“55 maize hybrids”
Title
Credible Intervals for Scores in the AMMI with Random Effects for Genotype
Luciano Antonio de Oliveira; Carlos Pereira da Silva; Joel Jorge Nuvunga; et al. Crop Science 2015. doi:10.2135/cropsci2014.05.0369
Other claims from this paper (4)
- Method / resource Credible intervals identified genotypes and environments that did not contribute to genotype by environment interaction.
- Method / resource The method identified homogeneous subgroups and genotype adaptability to specific environments.
- Method / resource Posterior distributions of singular vectors were bimodal with equal absolute density peaks.
- Method / resource Random genotype effects enabled Bayesian AMMI to accommodate additive and nonadditive relationship matrices.