Affiliation:
1. Universidade de São Paulo, Brazil
2. Instituto Federal de Educação, Ciência e Tecnologia - Sul de Minas Gerais, Brazil
3. USP, Brazil
Abstract
The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.
Subject
Agronomy and Crop Science,Animal Science and Zoology
Reference29 articles.
1. Estimation of additive, maternal and non-additive genetic effects of preweaning growth traits in a multibreed beef cattle project;ABDEL-AZIZ M.;Animal Science Journal,2003
2. Environmental and genetic effects on weight, scrotal circumference and visual scores at weaning on Canchim beef cattle;BARICHELLO F.;Revista Brasileira de Zootecnia,2011
3. Conditioning diagnostics: collinearity and weak data in regression;BELSLEY D.A.,1991
4. Regression diagnostics: identifying influential data and sources of collinearity;BELSLEY D.A.,2004
5. Alternatives to least squares in multiple linear regression to predict production traits;BERGMANN J.A.G.;Journal of Animal Breeding and Genetics,1995
Cited by
11 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献