| Autor: |
Herawati, N., Fitriyani, A., Saidi, S., Setiawan, E., Meliantari, D. |
| Rok vydání: |
2023 |
| Předmět: |
|
| DOI: |
10.5281/zenodo.8031706 |
| Popis: |
The Poisson regression model is a statistical model that can be utilized to analyze the relationship between independent variable X in the structure of continuous, discrete or mixed data and dependent variable Y in the form of discrete data. This model has several assumptions that must be met, one of which is that the variance value of the dependent variable must be equal to the average (equidispersion). If the variance value is larger than the mean, data overdispersion will occur. This study will compare the performance of Quasi-Poisson regression, Zero Inflated Poisson (ZIP) and Zero Inflated Negative Binomial (ZINB) regression models on overdispersion data, namely filariasis cases data in east Lampung province, Indonesia. The results showed that the ZIP method was the best for modeling data overdispersion compared to Quasi-Poisson regression and ZINB method. This is indicated by the smallest QAIC, QAICc and RMSE values of the ZIP model when compared to the Quasi-Poisson and ZINB regression models. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
