PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2012 | 21 | 3 |

Tytuł artykułu

Zero-inflated regression models for modeling the effect of air pollutants on hospital admissions

Autorzy

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
Count regression methods are the fundamental tool used for modeling the association between environmental pollution and hospital admissions. Data with many zeros are often encountered in count regression models. Failure to account for the extra zeros may result in biased parameter estimates and misleading inferences. Zero-inflated Poisson and zero-inflated negative binomial regression models have been proposed for situations where the data generating process results in too many zeros.

Słowa kluczowe

Wydawca

-

Rocznik

Tom

21

Numer

3

Opis fizyczny

p.565-568,fig.,ref.

Twórcy

autor
  • Department of Statistics, University of Ondokuz Mayis, Istatistik Bolumu, 55139 Atakum-Samsun, Turkey

Bibliografia

  • 1. CONSUL P., JAIN G. A Generalization of the Poisson distribution, Technometrics. 15, 791,1973.
  • 2. CONSUL P., FAMOYE F. Generalized Poisson regression model, Commun. Stat. Theory. 21, 89, 1992.
  • 3. FAMOYE F., SINGH K.P. On inflated generalized Poisson regression model. Advances and Applications in Statistics, 3, 135, 2003.
  • 4. BAE S., FAMOYE F., WULU J.T., BATOLUCCİ A.A., SINGH K.P., A rich family of generalized Poisson regression models with applications. Mathematical and Computers in Simulation. 69, (1-2), 4, 2005.
  • 5. LAMBERT D. Zero-inflated Poisson regression with an application to defects in manufacturing, Technometrics, 34, 1, 1992.
  • 6. MARTIN T.G., WINTLE B.A., RHODES J.R., KUHNERT P.M., FIELD S.A., LOW-CHOY S.J., TYRE A.J., POSS- INGHAM H.P. Zero tolerance ecology: improving ecological inference by modelling the source of zero observations. Ecol. Lett. 8, 1235,2005.
  • 7. WENGER S.J., FREEMAN M.C. Estimating species occurrence, abundance, and detection probability using zeroinflated distributions. Ecology, 89, 2953, 2008.
  • 8. HILBE J.M. Negative Binomial Regressions, Second Edition, Cambridge University Press, 2011.
  • 9. AGARWAL D.K., GELFAND A.E., POUSTY S.C. Zero inflated models with application to spatial count data, Environ. Ecol. Stat., 9, 342, 2002.
  • 10. WARTON D.I. Many zeros does not mean zero inflation: comparing the goodness-of-fit of parametric models to multivariate abundance data. Environmetrics, 16, 275, 2005.
  • 11. POTTS J.M., ELITH J. Comparing species abundance models. Ecol. Model. 199, 153, 2006.
  • 12. LEWIN W., FREYHOF J., HUCKSTORF V., MEHNER T., WOLTER C. When no catches matter: coping with zeros in environmental assessments. Ecological Indicators 10, 572, 2009.
  • 13. EL-SHAARAWI A.H., ZHU R., JOE H. Modelling species abundance using the Poisson-Tweedie family. Environmetrics. 22, 152, 2011.
  • 14. MELLES S.J., FORTIN M.J., LINDSAY K., BADZINSKI D., MELLES S.J. Expanding northward: influence of climate change, forest connectivity, and population processes on a threatened species' range shift. Glob. Change Biol., 17, 17, 2010.
  • 15. VAUDOR L., LAMOUROUX N., OLIVIER J.M. Comparing distribution models for small samples of overdispersed counts of freshwater fish. Acta Oecol., 37, 170, 2011.
  • 16. ANDERSON H.R., SP1X C., MEDINA S„ SCHOUTEN J.P., CASTELLSAGUE J., ROSSI G., ZMIROU D., TOULOUMI G., WOJTYNIAK B., PONKA A, BACHAROVA L., SCHWARTZ J., KATSOUYANNI K. Air pollution and daily admissions for chronic obstructive pulmonary disease in 6 European cities: results from the aphea project. Eur. Respir. J. 10, 1064,1997.
  • 17. BURNETT R.T., DALES R., KREWSKI D., VINCENT R., DANN T., BROOK J.R. Associations between ambient particulate sulphate and admissions to Ontario Hospitals for cardiac and respiratory diseases. Am. J. Epidemiol. 142, 15, 1995.
  • 18. CHEN Y., YANG W., JENNISON B.L., OMAYE S.T. Air particulate pollution and hospital admissions for chronic obstructive pulmonary disease in reno, Nevada. Inhal. Toxicol. 12, 281,2000.
  • 19. CHEN Y., YANG Q., KREWSKI D., SHI Y., BURNETT R.T., MCGRAIL K. Influence of relatively low level of particulate air pollution on hospitalization for coped in elderly people. Inhal. Toxicol. 16, 21, 2004.
  • 20. DOMINICI F., PENG R.D., BELL M.L. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA. 295, 1127, 2006.
  • 21. YANG C., CHEN C. Air pollution and hospital admissions for chronic obstructive pulmonary disease in a subtropical city: Taipei, Taiwan. J Toxicol. Env. Heal A, 70, 1214, 2007.
  • 22. TERZI Y., CENGIZ M.A. Using of generalized additive model for npdel selection in multiple Poisson regression for air pollution data. Scientific Research and Essay. 4, (9), 867, 2009.
  • 23. AKAIKE H., A new look at the statistical model identification, IEEE T. Automat. Contr., 19, (6), 716,1974.
  • 24. SCHWARZ G.E., Estimating the dimension of a model, Ann. Stat. 6, (2), 461, 1978.
  • 25. FAMOYE F., SINGH K.P. Zero-truncated generalized Poisson regression model with an application to domestic violence. Journal of Data Science. 4, 117, 2006.
  • 26. WINKELMANN R. Econometric Analysis of Count Data, Fifth Edition, New York: Springer, 2008.

Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

bwmeta1.element.agro-0f8e8b22-8cb4-449e-ab56-e83be790296f
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.