References
- Böhning D, Dietz E, Schlattmann P, et al. The zero-inflated poisson model and the decayed, missing and filled teeth index in dental epidemiology. J R Stat Soc Ser A (Stat Soc). 1999;162(2):195–209.
- Zhou XH, Tu W. Confidence intervals for the mean of diagnostic test charge data containing zeros. Biometrics. 2000;56(4):1118–1125.
- Agarwal D, Gelfand A, Citron-Pousty S. Zero-inflated models with application to spatial count data. Environ Ecol Stat. 2002;9(4):341–355.
- Hall D. Zero-inflated poisson and binomial regression with random effects: a case study. Biometrics. 2000;56(4):1030–1039.
- Lambert D. Zero-inflated poisson regression, with an application to defects in manufacturing. Technometrics. 1992;34(1):1–14.
- Desjardins CD. Modeling zero-inflated and overdispersed count data: an empirical study of school suspensions. J Exp Educ. 2016;84(3):449–472.
- Heilbron DC. Zero-altered and other regression models for count data with added zeros. Biom J. 1994;36(5):531–547.
- Sposto R, Preston DL, Shimizu Y, et al. The effect of diagnostic misclassification on non-cancer and cancer mortality dose response in A-bomb survivors. Biometrics. 1992;48(2):605–617.
- Anderson C, Bratcher T, Kutran K. Bayesian-estimation of population-density and visibility. Tex J Sci. 1994;46(1):1–12.
- Fader PS, Hardie BGS. A note on modelling underreported poisson counts. J Appl Stat. 2000;27(8):953–964.
- Bratcher TL, Stamey JD. Estimation of poisson rates with misclassified counts. Biom J. 2002;44(8):946–956.
- Stamey JD, Young DM, Cecchini M. A double-sampling approach for maximum likelihood estimation for a Poisson rate parameter with visibility-biased data. Statistica. 2003;63(1):3–11.
- Stamey JD, Young DM, et al. Bayesian predictive probability functions for count data that are subject to misclassification. Biom J. 2004;46(5):572–578.
- Stamey JD, Young DM, Boese D. A Bayesian hierarchical model for Poisson rate and reporting-probability inference using double sampling. Aust N Z J Stat. 2006;48(2):201–212.
- Stamey JD, Young DM. Maximum likelihood estimation for a Poisson rate parameter with misclassified counts. Aust N Z J Stat. 2005;47(2):163–172.
- Stamey JD, Young DM, Seaman JW. A Bayesian approach to adjust for diagnostic misclassification between two mortality causes in Poisson regression. Stat Med. 2008;27(13):2440–2452.
- Wu W, Stamey J, Kahle D. A Bayesian approach to account for misclassification and overdispersion in count data. Int J Environ Res Public Health. 2015;12(9):10648–10661.
- Famoye F, Singh KP. Zero-inflated generalized poisson regression model with an application to domestic violence data. J Data Sci. 2006;4(1):117–130.
- Guliani H, Gamtessa S, Çule M. Factors affecting tobacco smoking in ethiopia: evidence from the demographic and health surveys. BMC Public Health. 2019;19(1):938–954.
- Handebo S, Birara S, Kassie A, et al. Smoking intensity and associated factors among male smokers in ethiopia: further analysis of 2016 ethiopian demographic and health survey. Biomed Res Int. 2020;2020:1–7.
- Johnson NL, Kemp AW, Kotz S. Univariate discrete distributions. 3rd . New York: John Wiley&Sons; 2005.
- Sengupta D, Banerjee T, Roy S. Estimation of poisson mean with under-reported counts: a double sampling approach. Aust N Z J Stat. 2020;62(4):508–535.
- Mullahy J. Specification and testing of some modified count data models. J Econom. 1986;33(3):341–365. Available from: https://EconPapers.repec.org/RePEc:eee:econom:v:33:y:1986:i:3:p:341-365