Analysis of litter size and average litter weight in pigs using a recursive model

A - Papers appearing in refereed journals

Varona, L., Sorensen, D. and Thompson, R. 2007. Analysis of litter size and average litter weight in pigs using a recursive model. Genetics. 177 (3), pp. 1791-1799.

AuthorsVarona, L., Sorensen, D. and Thompson, R.

An analysis of litter size and average piglet weight at birth in Landrace and Yorkshire using a standard two-trait mixed model (SMM) and a recursive mixed model (RMM) is presented. The RMM establishes a one-way link from litter size to average piglet weight. It is shown that there is a one-to-one correspondence between the parameters of SMM and RMM and that they generate equivalent likelihoods. As parameterized in this work, the RMM tests for the presence of a recursive relationship between additive genetic values, permanent environmental effects, and specific environmental effects of litter size, on average piglet weight. The equivalent standard mixed model tests whether or not the covariance matrices of the random effects have a diagonal structure. In Landrace, posterior predictive model checking supports a model without any form of recursion or, alternatively, a SMM with diagonal covariance matrices of the three random effects. In Yorkshire, the same criterion favors a model with recursion at the level of specific environmental effects only, or, in terms of the SMM, the association between traits is shown to be exclusively due to an environmental (negative) correlation. It is argued that the choice between a SMM or a RMM should be guided by the availability of software, by ease of interpretation, or by the need to test a particular theory or hypothesis that may best be formulated under one parameterization and not the other.

Year of Publication2007
Journal citation177 (3), pp. 1791-1799
Digital Object Identifier (DOI)doi:10.1534/genetics.107.077818
Open accessPublished as non-open access
Funder project or codeCentre for Mathematical and Computational Biology (MCB)
Research in statistics relevant to biological processes
Output statusPublished
Publication dates
Print01 Nov 2007
Publication process dates
Accepted16 Aug 2007
Copyright licensePublisher copyright
PublisherGenetics Society of America (GSA)

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