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Pesquisa Agropecuária Brasileira
Article . 2012
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Degree of multicollinearity and variables involved in linear dependence in additive-dominant models Grau de multicolinearidade e variáveis envolvidas na dependência linear em modelos aditivo-dominantes

Authors: Juliana Petrini; Raphael Antonio Prado Dias; Simone Fernanda Nedel Pertile; Joanir Pereira Eler; José Bento Sterman Ferraz; Gerson Barreto Mourão;

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models Grau de multicolinearidade e variáveis envolvidas na dependência linear em modelos aditivo-dominantes

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.O objetivo deste trabalho foi avaliar o grau de multicolinearidade e identificar as variáveis envolvidas na dependência linear em modelos aditivo-dominantes. Foram utilizados dados de peso ao nascimento (n=141.567), peso ao ano (n=58.124) e perímetro escrotal (n=20.371) de bovinos de corte compostos Montana Tropical. O diagnóstico de multicolinearidade foi baseado no fator de inflação de variância (VIF) e no exame dos índices de condição e dos autovalores da matriz de correlações entre as variáveis explanatórias. O primeiro modelo estudado (RM) incluiu o efeito fixo de classe de idade da mãe ao parto e as covariáveis associadas aos efeitos aditivos e não aditivos diretos e maternos. O segundo modelo (R) incluiu todos os efeitos do RM, exceto os efeitos aditivos maternos. Detectou-se multicolinearidade em ambos os modelos para todas as características consideradas, com valores de VIF de 1,03 - 70,20, para RM, e de 1,03 - 60,70, para R. As colinearidades aumentaram com o aumento de variáveis no modelo e com a redução no volume de observações, e foram classificadas como fracas, com valores de índice de condição entre 10,00 e 26,77. Em geral, as variáveis associadas aos efeitos aditivos e não aditivos estiveram envolvidas em multicolinearidade, parcialmente em razão da ligação natural entre essas covariáveis como frações dos tipos biológicos na composição racial.

Keywords

Agriculture (General), animal breeding, Bos taurus x Bos indicus, S1-972, beef cattle, matriz de correlação, correlation matrix, variance inflation factor, fator de inflação da variância, crossbreeding, melhoramento animal, bovino de corte, cruzamento

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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