Seleção da matriz de variância-covariância residual na análise de ensaios varietais com medidas repetidas em cana-de-açúcar
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Data
2015-06
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Resumo
This study aimed to evaluate different residual
structures of variance-covariance matrix (Σ), regarding the fitting of longitudinal data via mixed models in variety trials of sugarcane.
The adequate choice of this matrix provides most representative
models to the data. In each model was also evaluated the effects
of treatments (varieties), either as fixed or as random. Four trials
were carried out in three locations in the Goiás State, Brazil,
from 2005 to 2009. Each experiment was designed in randomized
complete block with three or four repetitions. The response variable
analyzed was tons of stalks per hectare (TCH). The goodness of
fitting of the different models to the data was assessed by Akaike
information criterion (AIC) and by likelihood ratio test (LRT).
This last statistic was used only to compare nested models, two by
two. It was observed that classic model in split-plot design ranged
among the worst or with just median adjustments. The structures of
Σ matrix with the best fittings to the data varied among trials, with
outstanding for the unstructured matrix. These results show that
the structure of independent errors, in general, is not adequate for
these analyses, and a prior definition of the co-variance structure
can lead to unreliable results for these trials. Small changes
were observed in the ranking of these structures by assuming the
treatment effects as fixed or random, however, without significant
effects on the ranking of the best structures in each trial.
Descrição
Palavras-chave
Saccharum spp., Dados longitudinais, Estruturas de covariância, Modelos mistos, Genótipos aleatórios, Longitudinal data, Covariance structures, Mixed models, Random genotypes
Citação
SILVA, Emerson Noleto; DUARTE, João Batista; REIS, Américo José Dos Santos. Seleção da matriz de variância-covariância residual na análise de ensaios varietais com medidas repetidas em cana-de-açúcar. Ciência Rural, Santa Maria, v. 45, n. 6, p. 993-999, jun. 2015.