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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21022

Title: Quantifying the genetic contribution to the variability of count traits
Authors: Oliveira, Izabela R.C.
Molenberghs, Geert
Demétrio, C.G.B.
Dias, Carlos T.S.
Souza, Claudio L.
Issue Date: 2015
Citation: Friedl, Herwig; Wagner, Helga (Ed.). Proceedings of the 30th International Workshop on Statistical Modelling, p. 314-318
Abstract: Heritability is a important concept in animal and plant breeding, as it is in human biological applications. It is quantified based on fitting a model to hierarchical data. For data where linear models can be used, this attribute is conveniently defined as a ratio of variance components. Matters are less simple for non-Gaussian outcomes. The focus here is on count outcomes where extensions of the Poisson model are used to describe the data. Expressions for heritability of count traits are derived using the so-called Poisson combined model, which combines a Poisson outcome distribution with normal as well as gamma random effects, to capture both correlation among repeated observations as well as overdispersion, and admits closed-form expressions for the mean, variances and, hence, ratio of variances. It thus flexibly accommodates overdispersion and within-unit correlation. The proposed methodology is illustrated using maize data from a plant breeding program and compared with the usual, but questionable analysis using linear mixed models.
URI: http://hdl.handle.net/1942/21022
Category: C2
Type: Proceedings Paper
Appears in Collections: Research publications

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