Abstract
Poisson regression can be used to analyze count data, with assuming equidispersion. However, in the case of overdispersion often occur in the count data. The implementation of Poisson Regression can not be applied on this data because the data having overdispersion, that will lead to underestimate the standard error. Thus, use Quasi-Likelihood regression on this data. Quasi-Likelihood regression was also could not handle the overdispersion, but Quasi-Likelihood regression can improve the value of the standard error becomes greater than the value of the standard error on Poisson regression. Thus, by using the Quasi-Likelihood regression obtained three independent variables that affect the number of divorce cases in each urban city of Denpasar in 2011.
Highlights
Poisson regression can be used to analyze count data, with assuming equidispersion
in the case of overdispersion often occur in the count data
The implementation of Poisson Regression can not be applied on this data because the data having overdispersion
Summary
Poisson regression can be used to analyze count data, with assuming equidispersion. in the case of overdispersion often occur in the count data. Overdispersi dapat dideteksi dari rasio dispersinya, yang diukur dari nilai Deviance pada data, dengan hipotesis uji: H0 ∶ α = 1 H1 ∶ α > 1
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