Multiple linear regression models based on principal component scores to predict slaughter weight of broiler
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Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Eugen Ulmer Gmbh Co
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The aim of this study was to predict slaughter weight of male chickens by using principal component scores in multiple regression analysis. Chickens were raised under two different stocking densities. Four weeks age of body measurements were used as predictor variables. Two different approaches were used for those aims. In the first approach, only one selected score value obtained by principal component analysis was used for the prediction of slaughter weight. In the second approach, all six score values obtained from principal component analysis were used as independent variables. As a result, it was observed that using raw data of the study for the regression analysis for both groups resulted in a multicolinearity problem. On the other hand, when the principal component analysis completed on independent variables and the principal component scores analyzed together with independent variables were used for the multiple regression analysis, that problem diminished.
Açıklama
Anahtar Kelimeler
Broiler, body measurements, multiple linear regression analysis, principal component analysis
Kaynak
Archiv Fur Geflugelkunde
WoS Q Değeri
Q3
Scopus Q Değeri
Cilt
73
Sayı
2
