Research

Modeling relationships between calving traits: a comparison between standard and recursive mixed models

Evangelina López de Maturana^1,2 , Gustavo de los Campos¹ , Xiao-Lin Wu³ , Daniel Gianola^1,3,4 , Kent A Weigel³ and Guilherme JM Rosa³

¹  Department of Animal Sciences, University of Wisconsin, Madison, 53706, USA

²  Departamento de Mejora Genética Animal, INIA, Carretera de La Coruña km 7.5, 28040 Madrid, Spain

³  Department of Dairy Science, University of Wisconsin, Madison, 53706, USA

⁴  Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, 53706, USA

author email corresponding author email

Genetics Selection Evolution 2010, 42:1doi:10.1186/1297-9686-42-1

Published:	25 January 2010

Abstract

Background

The use of structural equation models for the analysis of recursive and simultaneous relationships between phenotypes has become more popular recently. The aim of this paper is to illustrate how these models can be applied in animal breeding to achieve parameterizations of different levels of complexity and, more specifically, to model phenotypic recursion between three calving traits: gestation length (GL), calving difficulty (CD) and stillbirth (SB). All recursive models considered here postulate heterogeneous recursive relationships between GL and liabilities to CD and SB, and between liability to CD and liability to SB, depending on categories of GL phenotype.

Methods

Four models were compared in terms of goodness of fit and predictive ability: 1) standard mixed model (SMM), a model with unstructured (co)variance matrices; 2) recursive mixed model 1 (RMM1), assuming that residual correlations are due to the recursive relationships between phenotypes; 3) RMM2, assuming that correlations between residuals and contemporary groups are due to recursive relationships between phenotypes; and 4) RMM3, postulating that the correlations between genetic effects, contemporary groups and residuals are due to recursive relationships between phenotypes.

Results

For all the RMM considered, the estimates of the structural coefficients were similar. Results revealed a nonlinear relationship between GL and the liabilities both to CD and to SB, and a linear relationship between the liabilities to CD and SB.

Differences in terms of goodness of fit and predictive ability of the models considered were negligible, suggesting that RMM3 is plausible.

Conclusions

The applications examined in this study suggest the plausibility of a nonlinear recursive effect from GL onto CD and SB. Also, the fact that the most restrictive model RMM3, which assumes that the only cause of correlation is phenotypic recursion, performs as well as the others indicates that the phenotypic recursion may be an important cause of the observed patterns of genetic and environmental correlations.