Zulki Alwani, Z. I. and Ibrahim, A. I. N. and Yunus, R. M. and Yusof, F. (2021) Application of zerotruncated count data regression models to airpollution disease. In: 28th Simposium Kebangsaan Sains Matematik, SKSM 2021, 28  29 July 2021, Kuantan, Pahang, Virtual.

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Official URL: http://dx.doi.org/10.1088/17426596/1988/1/012096
Abstract
Count data consist of nonnegative integers that have many applications in various fields of studies. To handle count data, there are various statistical models that can be employed corresponding to the properties of the count data studied. Poisson regression model (PRM) is mostly used to model data with equidispersion, while negative binomial regression model (NBRM) is a model that is regularly employed to model overdispersed count data. On the other hand, the usual count data regression models may not able to handle strictly positive counts. In this case, the appropriate model for the analysis of such data would be models truncated at zero. We are interested to study the relationship between pollution related disease with influential factors such as air pollution and climate variables in Johor Bahru, Malaysia, using these zerotruncated models, where the number of disease cases are strictly positive. In particular, the zerotruncated PRM and NBRM are used to determine the association between the number of dengue patients and their influential factors. From the study, zerotruncated NBRM is found to be the best model amongst the two models to model the relationship between the number dengue cases and air pollution and climate. Air pollution factors that significantly affect the number of cases for dengue are particulate matter (PM10) and sulfur dioxide. Also, humidity and temperature are the climate factors that significantly affect the number of dengue cases.
Item Type:  Conference or Workshop Item (Paper) 

Uncontrolled Keywords:  Poisson regression model (PRM), models truncated, air pollution 
Subjects:  Q Science > QA Mathematics 
Divisions:  Science 
ID Code:  98089 
Deposited By:  Widya Wahid 
Deposited On:  30 Nov 2022 04:14 
Last Modified:  30 Nov 2022 04:14 
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