Abstract
The Poisson regression is generally used to analyze the response variable that is a discrete data. Poisson regression has assumption which must be met, that is condition equidispersion. But in fact this assumption is often violated, that is the value of the variance is greater or less than the mean value. The condition when value of the variance is greater than the mean value is called overdispersion. One method that can be used for overdispersion data is Generalized Poisson regression. In this research, it was found that the Generalized Poisson regression method was better than Poisson regression method.
Highlights
that is the value of the variance is greater
The condition when value of the variance is greater than the mean value is called overdispersion
One method that can be used for overdispersion data is
Summary
Jika terjadi fenomena overdispersi pada data, maka regresi Poisson kurang akurat digunakan untuk analisis, karena berdampak pada nilai standard error menjadi under estimate (lebih kecil dari nilai sesungguhnya), sehingga kesimpulan yang diperoleh menjadi tidak valid (McCullagh & Nelder [2]). Untuk mengatasi masalah overdispersi tersebut, salah satu metode yang dapat digunakan adalah analisis regresi Generalized Poisson yang merupakan perluasan dari regresi Poisson.
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