Detecting overdispersion in count data: A zero-inflated Poisson regression analysis
Open accessAbstract
This study focusing on analysing count data of butterflies communities in Jasin, Melaka. In analysing count dependent variable, the Poisson regression model has been known as a benchmark model for regression analysis. Continuing from the previous literature that used Poisson regression analysis, this study comprising the used of zero-inflated Poisson (ZIP) regression analysis to gain acute precision on analysing the count data of butterfly communities in Jasin, Melaka. On the other hands, Poisson regression should be abandoned in the favour of count data models, which are capable of taking into account the extra zeros explicitly. By far, one of the most popular models include ZIP regression model. The data of butterfly communities which had been called as the number of subjects in this study had been taken in Jasin, Melaka and consisted of 131 number of subjects visits Jasin, Melaka. Since the researchers are considering the number of subjects, this data set consists of five families of butterfly and represent the five variables involve in the analysis which are the types of subjects. Besides, the analysis of ZIP used the SAS procedure of overdispersion in analysing zeros value and the main purpose of continuing the previous study is to compare which models would be better than when exists zero values for the observation of the count data. The analysis used AIC, BIC and Voung test of 5% level significance in order to achieve the objectives. The finding indicates that there is a presence of over-dispersion in analysing zero value. The ZIP regression model is better than Poisson regression model when zero values exist.
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Overdispersion was tested by comparing whether the variance exceeded the mean.
“Overdispersion was tested by comparing whether the variance exceeded the mean [55].”
From Predictors of antenatal care utilization among the Rohingya population in the refugee camps of Cox's Bazar, Bangladesh (2025) · cites this paper as [55]
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Analysing count data of Butterflies communities in Jasin, Melaka: A Poisson regression analysis
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“Overdispersion was tested by comparing whether the variance exceeded the mean [55].”
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- Authors
- Muhamad Jamil, S. A., Abdullah, M. A. A., Kek, S. L., Nor, M. E., Mohamed, M., & Ismail, N.
- Affiliations
- Tun Hussein Onn University of Malaysia (MY)
- Venue
- Journal of Physics: Conference Series
- Publisher
- IOP Publishing
- Published
- 2017-09
- Volume
- 890
- Pages
- 012170
- ISSN
- 1742-6588 (ISSN-L)
- 1742-6596
- OpenAlex
- W2759839044
- Cited by
- 8
- References
- 11
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2022: 1 · 2021: 3 · 2020: 1
- FWCI
- 0.57
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Journal of Physics Conference Series (publishedVersion, cc-by)
- Funders
- Universiti Tun Hussein Onn Malaysia
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- overdispersion, count data, zero-inflated Poisson regression, Poisson regression, butterfly communities, model comparison, AIC and BIC
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