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.
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.

  1. Agarwal, D.K., Gelfand, A.E., Pousty, S.C. (2002). Zero-inflated models with application to spatial count data. Environmental and Ecological Statistics. 9: 341-355. DOI: 10.1023/ A:1020910605990.

  2. Berglund, B. and Philipsson, J. (1992). Increasing Stillbirth Rate in the Swedish Friesian Population. Proceedings of the 43rd Annual Meeting EAAP. Madrid, Spain.

  3. Berglund, B. (1996). Ongoing Research on the Causes of Variation in Calving Performance and Stillbirths in Swedish Dairy Cattle. Interbull Bulletin. 12: 78-83. 

  4. Böhning, D., Dietz, E., Schlattmann, P. (1999). The zero inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology. Journal of the Royal Statistical Society A. 162: 195-209. DOI: 10.1111/1467-985X.00130.

  5. Cox, D.R. (1983). Some remarks on overdispersion. Biometrika. 70(1): 269-274. DOI: 10.2307/2335966.

  6. Dalrymple, M.L., Hudson, I.L., Ford, R.P.K. (2003). Finite mixture, zero-inflated poisson and hurdle models with application to SIDS. Computational Statistics and Data Analysis. 41: 491-504. DOI: 10.1016/S0167-9473(02)00187-1.

  7. Eriksson, S. Näsholm, A., Johansson, K., Philipsson, J. (2004). Genetic parameters for calving difficulty, stillbirth and birth weight for Hereford and Charolais at first and later parities. Journal of Animal Science. 82: 375-383. DOI: 10.2527/ 2004.822375x.

  8. Famoye, F. and Karan, P.S. (2006). Zero-inflated generalized Poisson regression model with an application to domestic violence data. Journal of Data Science. 5(4): 117-130.

  9. Garaya, A.M., Hashimotob, E.M., Ortegab, E.M.M, Lachos, L.H. (2011). On estimation and influence diagnostics for zero-inflated negative binomial regression models. Computational Statistics and Data Analysis. 55(3): 1304-1318. DOI: 10.10 16/j.csda.2010.09.019.

  10. Gevrekçi, Y., Chang, Y., Kızılkaya, K., Gianola, D., Weigel, K., Akbaş, Y. (2006). Bayesian inference for calving ease and stillbirth in Holsteins using a bivariate threshold sire-maternal grandsire model. Proceedings of 8th World Congress of Genetics Applied to Livestock Production. Belo Horizonte, Brazil.

  11. Gevrekçi, Y. (2006). Estimation of genetic parameters of calving ease and stillbirth as threshold traits by using Gibbs Sampling. PhD Thesis. Ege University, Turkey.

  12. Greene, W.H. (1994). Accounting for excess zeros and sample selection in Poisson and negative binomial regression models. Working Paper. Department of Economics, New York University. pp. 94-10, 

  13. Hall, D.B. (2000). Zero inflated poisson and binomial regression with random effects: A case study. Biometrics. 56(4): 1030-1039.  

  14. Hilbe, J.M. (2007). Negative Binomial Regression. Cambridge University Press, Cambridge, UK. DOI: 10.1017/CBO9780511973420.

  15. Kokate, L.S., Singh, A., Banu, R., Gandhi, R.S., Chakravarty, A. K., Gupta, A.K., Sachdeva, G.K. (2014). Prediction of 305-day lactation milk yield based on bimonthly test day values in Karan Fries cattle. Indian Journal of Animal Research. 48(2):103-105. DOI: 10.5958/j.0976-0555.48.2.023.

  16. Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics. 34(1): 1-13. DOI: 10.1080/00401706.1992.10485228.

  17. Meyer, C.L., Berger, P.J., Koehler, K.J., Thompson, J.R., Sattler, C.G. (2001). Phenotypic trends in incidence of stillbirth for Holsteins in the United States. Journal of Dairy Science. 84: 515-523. DOI: 10.3168/jds.S0022-0302(01)74502-X.

  18. Nehara, M., Singh, A., Gandhi, R.S., Chakravarty, A.K., Gupta, A.K., Sachdeva, G.K. (2013). Phenotypic, genetic and environmental trends in milk yield and milk production efficiency traits in Karan Fries cattle. Indian Journal of Animal Research. 47: 402-06.

  19. Philipsson, J., Steinbock, L., Berglund, B. (1998). Considering stillbirths in the breeding program. Interbull Bulletin. 18: 25-27.

  20. Pittman, B., Buta, E., Krishnan-Sarin, S., O’Malley, S.S., Liss, T., Gueorguieva, R. (2018). Models for analyzing zero- inflated and overdispersed count data: an application to cigarette and marijuana use. Nicotine and Tobacco Research. 22(8): 1390-1398. DOI: 10.1093/ntr/nty072.

  21. Steinbock, L., Gates, P., Berglund, B., Philipsson, J. (1997). Direct and maternal genetic effects on stillbirths at different parities in Swedish Holsteins. Proceedings of 48th Annual Mtg. EAAP. Vienna, Austria. 

  22. Takma Ç., İşçi Güneri Ö., Gevrekçi Y. (2016). Investigation of stillbirth rate using Logistic Regression Analysis in Holstein Friesian calves. Journal of Agriculture Faculty of Ege University. 53: 245-250. DOI: 10.20289/zfdergi. 389278.

  23. Yeşilova, A., Kaydan, B., Kaya, Y. (2010). Modelling insect-egg data with excess zeros using zero-inflated regression models. Hacettepe Journal of Mathematics and Statistics. 39(2): 273-282. 

  24. Yeşilova, A. and İnanç, D.E. (2016). Modeling mite counts using Poisson and negative binomial regressions. Fresenius Environmental Bulletin. 25: 5062-5066. DOI: 10.18805/ ijare.v50i6.6674.

  25. Zaborski, D., Grzesiak, W., Kotarska, K., Szatkowska, I., Jedrzejczak, M. (2014). Detection of difficult calvings in dairy cows using boosted classification trees. Indian Journal of Animal Research. 48: 452-458.

  26. Zeileis, A., Kleiber, C., Jackman, S. (2007). Regression models for count data in R. Journal of Statistical Software. 27: 1-25. DOI: 10.18637/jss.v027.i08.

  27. Zhou, X. and Tu, W. (2000). Confidence intervals for the mean of diagnostic test charge data containing zeros. Biometrics. 56(4): 1118-1125. 

  28. Zhuo, L., Stacey, K., Lawrence, J.C., Lisa, K.H., Richard, H.L.M.O. (2008). Modeling motor vehicle crashes for street racers using zero-inflated models. Accident Analysis and Prevention. 40: 835-839. DOI: 10.1016/j.aap.2007.09.022.

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