Salmonella is one of the major sources of toxin-infection in humans worldwide and is due to transmission of pathogens via pork. This paper aims at investigating the effect of season and animal weight on SP-ratio. Pigs were sampled from different herds and SP-ratios were measured and categorized into two different groups. Depending on the categorization of the response and whether or not clustering is taken into account, different binary logistic and multicategory logit models were considered. Without taking clustering into account, ordinary logistic regression, adjacent logit, continuation-ratio logit and proportional odds model were fitted. GEE and GLMM were considered to correct for the herd-effect. Among the multicategory logit models, the proportional odds model is preferred, since it did not reject the assumption of common slopes. However, regarding the goodness-of-fit test, this model did not adequately fit the data. Both GEE and GLMM have their advantages, depending on the specific focus and question of interest. In all models, the interaction between weight and season was not significant. Weight was found significant, while season was insignificant in all models. As it was expected, weight as indicator for age was found to have a significant effect on SP-ratios.
| Published in | American Journal of Theoretical and Applied Statistics (Volume 5, Issue 3) |
| DOI | 10.11648/j.ajtas.20160503.12 |
| Page(s) | 87-93 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Salmonella, SP-ratios, Logit Models, GEE, GLMM, Herd-Effect
| [1] | Chin, J. (2000). Control of communicable diseases manual (Vol. 17). Washington, DC: American Public Health Association. |
| [2] | Hoelzer, K., Moreno Switt, A. I., & Wiedmann, M. (2011). Animal contact as a source of human non-typhoidal salmonellosis. Vet res, 42(1), 34. |
| [3] | Mead, P. S., Slutsker, L., Dietz, V. McCaig, L. F., Bresee, J. S., Shapiro, C., Griffn, P. M. and Tauxe, R. V. (1999). Food-related illness and death in the United States. Emerging Infectious Diseases, 5(5), 607-625. |
| [4] | Thorns, C. J. (2000). Bacterial food-borne zoonoses. Review Scientific et Technique (International Office of Epizootics), 19(5), 226-239. |
| [5] | NRRS (2005). National Reference Centre for Salmonella and Shigella: Annual report. Retrieved from http: //www.iph.fgov.be/bacterio/iframes/rapports/2004/Salm 2004 NL cover.pdf. |
| [6] | Delgado CL, Rosegrant MW, Meijer S. 2001. Livestock to 2020: the revolution continues. Auckland, New Zealand: Intl. Trade Research Consortium (IATRC). |
| [7] | Baer, Arica A. and Miller, Michael J. and Dilger, Anna C. (2013). Pathogens of Interest to the Pork Industry: A Review of Research on Interventions to Assure Food Safety. Comprehensive Reviews in Food Science and Food Safety, 12(2), 183-217. |
| [8] | CDC (Centers for Disease Control and Prevention): Preliminary Food Net data on the incidence of infection with pathogens transmitted commonly through food - 10 states. MMWR Morb Mortal Wkly Rep 2009, 59(14):418-422. |
| [9] | CDC. 2011. CDC estimates of foodborne illness in the United States. Center for Disease Control. Available from: http://www.cdc.gov/foodborneburden/2011-foodborne-estimates.html. |
| [10] | Bollaerts, K., Aerts, M., Ribbens, S., Van der Stede Y., Boone, I. and Mintiens, K. (2008). Identification of Salmonella high risk pig farms in Belgium using semi-parametric quantile regression. Journal of Royal Statistical Society (series A) 171(2), 449–464. |
| [11] | Molenberghs, G. and Verbeke, G. (2005). Models for discrete longitudinal data. New York: Springer. |
| [12] | Gerhard Tutz (1991). Sequential models in categorical regression. Computational Statistics & Data Analysis, 11(3), 275-295. |
APA Style
Isaac Akpor Adjei, Md. Rezaul Karim, Rachid Muleia, Peter Jouck. (2016). Dependency of the Distribution of Salmonella-Specific Antibodies SP-Ratios on Weight and Sampling Time. American Journal of Theoretical and Applied Statistics, 5(3), 87-93. https://doi.org/10.11648/j.ajtas.20160503.12
ACS Style
Isaac Akpor Adjei; Md. Rezaul Karim; Rachid Muleia; Peter Jouck. Dependency of the Distribution of Salmonella-Specific Antibodies SP-Ratios on Weight and Sampling Time. Am. J. Theor. Appl. Stat. 2016, 5(3), 87-93. doi: 10.11648/j.ajtas.20160503.12
AMA Style
Isaac Akpor Adjei, Md. Rezaul Karim, Rachid Muleia, Peter Jouck. Dependency of the Distribution of Salmonella-Specific Antibodies SP-Ratios on Weight and Sampling Time. Am J Theor Appl Stat. 2016;5(3):87-93. doi: 10.11648/j.ajtas.20160503.12
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Download@article{10.11648/j.ajtas.20160503.12,
author = {Isaac Akpor Adjei and Md. Rezaul Karim and Rachid Muleia and Peter Jouck},
title = {Dependency of the Distribution of Salmonella-Specific Antibodies SP-Ratios on Weight and Sampling Time},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {5},
number = {3},
pages = {87-93},
doi = {10.11648/j.ajtas.20160503.12},
url = {https://doi.org/10.11648/j.ajtas.20160503.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20160503.12},
abstract = {Salmonella is one of the major sources of toxin-infection in humans worldwide and is due to transmission of pathogens via pork. This paper aims at investigating the effect of season and animal weight on SP-ratio. Pigs were sampled from different herds and SP-ratios were measured and categorized into two different groups. Depending on the categorization of the response and whether or not clustering is taken into account, different binary logistic and multicategory logit models were considered. Without taking clustering into account, ordinary logistic regression, adjacent logit, continuation-ratio logit and proportional odds model were fitted. GEE and GLMM were considered to correct for the herd-effect. Among the multicategory logit models, the proportional odds model is preferred, since it did not reject the assumption of common slopes. However, regarding the goodness-of-fit test, this model did not adequately fit the data. Both GEE and GLMM have their advantages, depending on the specific focus and question of interest. In all models, the interaction between weight and season was not significant. Weight was found significant, while season was insignificant in all models. As it was expected, weight as indicator for age was found to have a significant effect on SP-ratios.},
year = {2016}
}
TY - JOUR T1 - Dependency of the Distribution of Salmonella-Specific Antibodies SP-Ratios on Weight and Sampling Time AU - Isaac Akpor Adjei AU - Md. Rezaul Karim AU - Rachid Muleia AU - Peter Jouck Y1 - 2016/04/26 PY - 2016 N1 - https://doi.org/10.11648/j.ajtas.20160503.12 DO - 10.11648/j.ajtas.20160503.12 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 87 EP - 93 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20160503.12 AB - Salmonella is one of the major sources of toxin-infection in humans worldwide and is due to transmission of pathogens via pork. This paper aims at investigating the effect of season and animal weight on SP-ratio. Pigs were sampled from different herds and SP-ratios were measured and categorized into two different groups. Depending on the categorization of the response and whether or not clustering is taken into account, different binary logistic and multicategory logit models were considered. Without taking clustering into account, ordinary logistic regression, adjacent logit, continuation-ratio logit and proportional odds model were fitted. GEE and GLMM were considered to correct for the herd-effect. Among the multicategory logit models, the proportional odds model is preferred, since it did not reject the assumption of common slopes. However, regarding the goodness-of-fit test, this model did not adequately fit the data. Both GEE and GLMM have their advantages, depending on the specific focus and question of interest. In all models, the interaction between weight and season was not significant. Weight was found significant, while season was insignificant in all models. As it was expected, weight as indicator for age was found to have a significant effect on SP-ratios. VL - 5 IS - 3 ER -
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