Indian Journal of Animal Research

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Comparison of Different Count Models for Investigation of Some Environmental Factors Affecting Stillbirth in Holsteins

Y. Gevrekçi, Ö.İ. Güneri, Ç. Takma, A. Yeşilova
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1Department of Animal Science, Faculty of Agriculture, University of Ege, Izmir, Turkey.
Cite article:- Gevrekçi Y., Güneri Ö.İ., Takma Ç., Yeşilova A. (2022). Comparison of Different Count Models for Investigation of Some Environmental Factors Affecting Stillbirth in Holsteins. Indian Journal of Animal Research. 56(9): 1158-1163. doi: 10.18805/IJAR.BF-1415.

ABSTRACT

Background: The objective of this study is comparing different count data models for stillbirth data. In modeling this type of data, Poisson regression or alternative models can be preferred.
Methods: The poisson, negative binomial, zero-inflated poisson, zero-inflated negative binomial, poisson-logit hurdle and negative binomial-logit hurdle regressions were compared and used to examine the effects of the gender, parity and herd-year-season independent variables on stillbirth. Furthermore, the Log-Likelihood statistics, Akaike Information Criteria, Bayesian Information Criteria and rootogram graphs were used as comparison criteria for performance of the models. According to these criteria, Negative Binomial-Logit Hurdle Regression model was chosen as the best model. 
Result: The parameter estimates obtained by Negative Binomial-Logit Hurdle Regression model in relation to the effects of the gender, parity and herd-year-season independent variables on stillbirth were found to be significant (p<0.01). It was found that while stillbirth incidence was higher in males than females, it was found to decrease as the parity increased. As a result, the Negative Binomial Logit Hurdle model was found the best model for stillbirth count data with overdispersion.

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