Using of Logistic Regression in Animal Science

Abstract

This study was carried out to examine the effects of environmental factors on different growth with Chi-square, G-test and logistic regression analysis after body weights of these growth periods were categorized as binary. Besides, logistic regression was also based on concordant statistics except Chi-square and G-tests as model fit criteria. With respect to three fit criteria, the relationships among categorized birth weight with categorized body weights in 45th, 60th and 75th days were significant (p<0.01). Moreover, the relationship between periods of the lambs born in early March of 2001 year by using logistic regression. The relationships between categorized body weights and categorized birth weight and/or environmental factors were analyzed sex and only categorized body weight in 75th day was significant (p<0.05). It could be said that birth weight, one of environmental factors, improved model fit more than the other factors when considered all model fit criteria in logistic regression.As a result, it can be suggested that in addition to Chi-square and G-tests used for providing relationship between two traits, logistic regression in terms of obtaining from different information will be an alternative analysis in place of variance analysis

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