COMPARISON OF POISSON, ZIP, ZINB, HURDLE AND ZIGP REGRESSION ANALYSIS METHODS IN SCHOOL-AGED SMOKING CASE MODELING IN KUDUS DISTRICT, CENTRAL JAVA

Elok Fitriani Rafikasari; Suci Ismadyaliana; Dwilaksana Abdullah Rasyid; Setiawan Setiawan

doi:10.53625/ijss.v1i3.5610

Authors

Elok Fitriani Rafikasari UIN Sayyid Ali Rahmatullah Tulungagung
Suci Ismadyaliana Institut Teknologi Sepuluh Nopember, Surabaya
Dwilaksana Abdullah Rasyid Institut Teknologi Sepuluh Nopember, Surabaya
Setiawan Setiawan Institut Teknologi Sepuluh Nopember, Surabaya

DOI:

https://doi.org/10.53625/ijss.v1i3.5610

Keywords:

Cigarette Consumption, Poisson, ZIP, ZINB, Hurdle, ZIGP, Vuong

Abstract

Smoking behavior among adolescents and children, especially boys, is increasing from time to time. This is very unfortunate considering the many harmful substances in cigarettes that can interfere with health. Modeling related to smoking cases for adolescents and school-age children is needed as a step to anticipate and deal with this problem. In this study we use the Poisson, ZIP, ZINB, Hurdle, and ZIGP regression methods to modeling the number of cigarettes consumed by adolescents and boys. The best model selection is done by the Vuong test. The results showed that the most suitable model was ZIGP with variables that had a significant effect on the amount of cigarette consumption in adolescents and children are age and education level

References

Badan Litbang Kesehatan, K. K. R. (2018). Laporan_Nasional_RKD2018_FINAL.pdf. In Badan Penelitian dan Pengembangan Kesehatan (p. 198). http://labdata.litbang.kemkes.go.id/images/download/laporan/RKD/2018/Laporan_Nasional_RKD2018_FINAL.pdf

BPS. (2020). Susenas Kor 2020. 26.

Cahyandari, R. (2014). Pengujian Overdispersi pada Model Regresi Poisson. Statistika, 14(2), 69–76. https://ejournal.unisba.ac.id/index.php/statistika/article/view/1204

Cragg, J. G. (1971). This content downloaded from 77.103.16.28 on Wed. 39(5), 829–844.

Czado, C., Erhardt, V., Min, A., & Wagner, S. (2007). Zero-inflated generalized Poisson models with regression effects on the mean, dispersion and zero-inflation level applied to patent outsourcing rates. Statistical Modelling, 7(2), 125–153. https://doi.org/10.1177/1471082X0700700202

Famoye, F., & Singh, K. P. (2021). Zero-Inflated Generalized Poisson Regression Model with an Application to Domestic Violence Data. Journal of Data Science, 4(1), 117–130. https://doi.org/10.6339/jds.2006.04(1).257

Garay, A. M., Hashimoto, E. M., Ortega, E. M. M., & Lachos, V. H. (2011). On estimation and influence diagnostics for zero-inflated negative binomial regression models. Computational Statistics and Data Analysis, 55(3), 1304–1318. https://doi.org/10.1016/j.csda.2010.09.019

Girik Allo, C. B., Otok, B. W., & Purhadi. (2019). Estimation Parameter of Generalized Poisson Regression Model Using Generalized Method of Moments and Its Application. IOP Conference Series: Materials Science and Engineering, 546(5). https://doi.org/10.1088/1757-899X/546/5/052050

Global Youth Tobacco Survey. (2020). Lembar Informasi Indonesia 2019 (Global Youth Tobacco Survei). World Health Organization, 1–2. https://www.who.int/indonesia/news/events/world-no-tobacco-day-2020

Ismail, N., & Jemain, A. A. (2007). Handling Overdispersion with Negative Binomial and Generalized Poisson Regression Models Casualty Actuarial Society Forum , Winter 2007. Society, 103–158. http://www.casualtyactuaries.com/pubs/forum/07wforum/07w109.pdf

Jansakul, N., & Hinde, J. P. (2002). Score test for zero-inflated poisson models. Computational Statistics and Data Analysis, 40(1), 75–96. https://doi.org/10.1016/S0167-9473(01)00104-9

Lambert, D. (1992). Zero-inflated poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14. https://doi.org/10.1080/00401706.1992.10485228

McGee, C. E., Trigwell, J., Fairclough, S. J., Murphy, R. C., Porcellato, L., Ussher, M., & Foweather, L. (2015). Influence of family and friend smoking on intentions to smoke and smoking-related attitudes and refusal self-efficacy among 9-10 year old children from deprived neighbourhoods: A cross-sectional study. BMC Public Health, 15(1), 15–21. https://doi.org/10.1186/s12889-015-1513-z

Mullahy, J. (1986). Specification and testing of some modified count data models. Journal of Econometrics, 33(3), 341–365. https://doi.org/10.1016/0304-4076(86)90002-3

Utami, N. (2020). Pengaruh Kebiasaan Merokok Orang Tua terhadap Perilaku Merokok Remaja Indonesia. Media Kesehatan Indonesia, 16(3), 327-335. DOI : 10.30597/mkmi.v16i3.9801

Shoukri, M. M. (1984). Maximum likelihood estimation for the generalized poisson distribution. Communications in Statistics - Theory and Methods, 13(12), 1533–1547. https://doi.org/10.1080/03610928408828776

Zeileis, A., Kleiber, C., & Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27(8), 1–25. https://doi.org/10.18637/jss.v027.i08