Count data distributions and their zero-modified equivalents as a framework for modelling microbial data with a relatively high occurrence of zero counts

International Journal of Food Microbiology

Volumn 136, Issue 3, 2010, Pages 268-277

  Gonzales Barron, Ursula ^a   Kerr, Marie ^b   Sheridan, James J ^a   Butler, Francis ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

^b ASHTOWN FOOD RESEARCH CENTRE   (Ireland)

Author keywords

Beef; Coliforms; Count distribution; Escherichia coli; Negative binomial; Poisson; Zero inflated

Indexed keywords

ARTICLE; BACTERIAL COUNT; BINOMIAL DISTRIBUTION; CARCASS; COLIFORM BACTERIUM; DATA ANALYSIS; DISPERSION; ESCHERICHIA COLI; GENETIC HETEROGENEITY; NONHUMAN; POISSON DISTRIBUTION; RISK ASSESSMENT; SLAUGHTERHOUSE; STATISTICS;

ABATTOIRS; ANIMALS; BINOMIAL DISTRIBUTION; CATTLE; COLONY COUNT, MICROBIAL; DATA INTERPRETATION, STATISTICAL; ENTEROBACTERIACEAE; ESCHERICHIA COLI; MEAT; MODELS, BIOLOGICAL; MODELS, STATISTICAL; POISSON DISTRIBUTION; RISK ASSESSMENT; STOCHASTIC PROCESSES;

BACTERIA (MICROORGANISMS); ESCHERICHIA COLI;

EID: 71749089411     PISSN: 01681605     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijfoodmicro.2009.10.016     Document Type: Article

References (30)

1. Boucher J.P., Denuit M., and Guillén M. Risk classification for claim counts: a comparative analysis of various zero-inflated mixed Poisson and hurdle models. North American Actuarial Journal 11 (2008) 110-131
2. Bulsara M.K., Holman C.D.J., Davies E.A., and Jones T.W. Evaluating risk factors associated with severe hypoglycemia in epidemiology studies - what method should we use?. Diabetic Medicine 21 (2004) 914-919
3. Cameron A.C., and Trivedi P.K. Count data models for financial data. In: Maddala G.S., and Rao C.R. (Eds). Handbook of Statistics. Statistical Methods in Finance vol. 14 (1996), Elsevier, Amsterdam 363-392
4. Cheung Y.B. Zero-inflated models for regression analysis of count data: a study of growth and development. Statistics in Medicine 21 (2002) 1461-1469
5. Gale P., van Dijk P.A.H., and Stanfield G. Drinking water treatment increases micro-organism clustering: the implications for microbiological risk assessment. Journal of Water Supply Research and Technology - Aqua 46 (1997) 117-126
6. Gardner W., Mulvey E.P., and Shaw E.C. Regression analyses of counts and rates: Poisson, overdispersed Poisson and negative binomial models. Psychological Bulletin 118 (1995) 392-404
7. Gill C., and Jones T. Setting control limits for Escherichia coli counts in samples collected routinely from pig or beef carcasses. Journal of Food Protection 69 (2006) 2837-2842
8. Gill C., McGinnis J., and Badoni M. Use of total Escherichia coli counts to assess the hygienic characteristics of a beef carcass dressing process. International Journal of Food Microbiology 31 (1996) 181-196
9. Gill C., Deslandes B., Rahn K., Houde A., and Bryant J. Evaluation of the hygienic performances of the processes for beef carcass dressing at 10 packing plants. Journal of Applied Microbiology 84 (1998) 1050-1058
10. Greene W. Econometric Analysis. 5th Edition (2002), Prentice Hall, Upper Saddle River, NJ 1026 pp
11. Hinde J., and Demetrio C. Overdispersion: models and estimation. Computational Statistics and Data Analysis 27 (1998) 151-170
12. Hirano S., Clayton M., and Upper C. Estimation of and temporal changes in means and variances of populations of Pseudomonas syringae on snap bean leaflets. Phytopathology 89 (1994) 934-940
13. Hornung R., and Reed L. Estimation of average concentration in the presence of nondetectable values. Applied Occupational and Environmental Hygiene 5 (1990) 46-51
14. Johnston M.D., Lambert R.J.W., Hanlon G.W., and Denyer S.P. A rapid method for assessing the suitability of quenching agents for individual biocides as well as combinations. Journal of Applied Microbiology 92 (2002) 784-789
15. Karlis D., and Ntzoufras I. Bivariate Poisson and diagonal inflated bivariate Poisson regression models in R. Journal of Statistical Software 14 10 (2005). http://www.jstatsoft.org/v14/i10 Available at: http://www.jstatsoft.org/v14/i10. Accessed 01 July 08
16. Lambert D. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics 34 (1992) 1-14
17. Lasta J., Rodriguez R., Zanelli M., and Margaria C.A. Bacterial count from bovine carcasses as an indicator of hygiene at slaughtering places: a proposal for sampling. Journal of Food Protection 54 (1992) 271-278
18. Lipsitz S.H., Kim K., and Zhao L. Analysis of repeated categorical data using generalized estimated equations. Statistics in Medicine 13 (1994) 1149-1163
19. Long J.S. Regression models for categorical and limited dependent variables (1997), Sage, Thousand Oaks, CA 328 pp
20. Lord D., Washington S.P., and Ivan J.N. Poisson, Poisson-gamma and zero-inflated regression models for motor vehicle crashes balancing statistical fit and theory. Accident Analysis and Prevention 37 (2005) 35-46
21. Masago Y., Oguma K., Katayama H., Hirata T., and Ohgaki S. Cryptosporidium monitoring system at a water treatment plant, based on waterborne risk assessment. Water Science Technology 50 (2004) 293-299
22. Min Y., and Agresti A. Random effect models for repeated measures of zero-inflated count data. Statistical Modelling 5 (2005) 1-19
23. Mullahy J. Specification and testing of some modified count data models. Journal of Econometrics 33 (1986) 341-365
24. Peltier M.R., Wilcox C.J., and Sharp D.C. Application of the Box-Cox data transformation to animal science experiments. Journal of Animal Science 76 (1998) 847-849
25. Pouillot R., Miconnet N., Afchain A., Delignette-Muller M., Beaufot A., Rosso L., Denis J., and Cornu M. Quantitative risk assessment of Listeria monocytogenes in French cold-smoked salmon: I. Quantitative exposure assessment. Risk Analysis 27 (2007) 683-700
26. Ridout M., Demetrio C., and Hinde J. Models for count data with many zeros. Proceedings of the XIX International Biometric Conference. 13-18 Dec. Cape Town, South Africa (1998) 13-18
27. Rouse D., Nordheim E., Hirano S., and Upper C. A model relating the probability of foliar disease incidence to the population frequencies of bacterial plant pathogens. Phytopathology 75 (1985) 505-509
28. Slymen D., Ayala G., Arredondo E., and Elder J.P. A demonstration of modelling count data with an application to physical activity. Epidemiology Perspectives and Innovations 3 3 (2006). http://www.epi-perspectives.com/content/3/1/3 Available at http://www.epi-perspectives.com/content/3/1/3. Accessed 15 July 08
29. Snedecor G.W., and Cochran W.G. Statistical Methods. 8th Edition (1989), Iowa State University Press
30. Zeileis A., Kleiber C., and Jackman S. Regression models for count data in R. Journal of Statistical Software 27 8 (2008). http://www.jstatsoft.org/v27/i08 Available at: http://www.jstatsoft.org/v27/i08. Accessed 08 October 08