4.3 Article

Meta-analysis of the experimental coefficient of variation in wheat using the Bayesian and Frequentist approaches

Journal

SCIENTIA AGRICOLA
Volume 80, Issue -, Pages -

Publisher

UNIV SAO PAULO, ESALQ
DOI: 10.1590/1678-992X-2021-0190

Keywords

Triticum aestivum L.; CVe probability distribution; Gamma distribution; credible and confidence interval

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In this study, the distribution and descriptive statistics of CVe were evaluated using Frequentist and Bayesian approaches. The results showed that the Bayesian and Frequentist analyses with the Gamma model yielded similar results for CVe, but the Bayesian credible intervals were narrower than the Frequentist confidence intervals.
A large set of variables is assessed for progeny selection in a plant-breeding program and other agronomic fields. The meta-analysis of the coefficient of variation (CVe) produces information for researchers and breeders on the experimental quality of trials. This analysis can also be applied in the decision-making process of the experimental plan regarding the experimental design, the number of repetitions, and the treatments and plants/progenies to be measured. In this study, we evaluated the dataset distribution and the descriptive statistics of CVe through the Frequentist and Bayesian approaches, aiming to establish the credibility and confidence intervals. We submitted CVe data of ten wheat (Triticum aestivum L.) traits reported in 1,068 articles published to the Bayesian and Frequentist analyses. Sample data were analyzed via Gamma and normal models. We selected the model with the lowest Akaike Information Criterion (AIC) value, and then we tested three link functions. In the Bayesian analysis, uniform distributions were used as non-informative priors for the Gamma distribution parameters with three ranges of theta similar to U (alpha,beta). Thus, the prior probability density function was given by: p(theta) = 1/beta-alpha, theta is an element of[alpha,beta]. The Bayesian and Frequentist approaches with the Gamma model presented similar results for CVe; however, the range Bayesian credible intervals was narrower than the Frequentist confidence intervals. Gamma distribution fitted the CVe data better than the normal distribution. The credible and confidence intervals of CVe were successfully applied to wheat traits and could be used as experimental accuracy measurements in other experiments.

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