Abstract: Poisson regression
was used to analyze the count data which Poisson distributed. Poisson
regression analysis requires state equidispersion, in which the mean value of
the response variable is equal to the value of the variance. However, there are
deviations in which the value of the response variable variance is greater than
the mean. This is called overdispersion. If overdispersion happens and Poisson
Regression analysis is being used, then underestimated standard errors will be
obtained. Negative Binomial Regression can handle overdispersion because it
contains a dispersion parameter. From the simulation data which experienced
overdispersion in the Poisson Regression model it was found that the Negative
Binomial Regression was better than the Poisson Regression model.
Keywords: Poisson Regression;
Overdispersion; Negative Binomial Regression; best model
Penulis: PUTU SUSAN PRADAWATI,
KOMANG GDE SUKARSA, I GUSTI AYU MADE SRINADI
Kode Jurnal: jpmatematikadd130014
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