Modeling of the number of divorce in Turkey using the Generalized Poisson, Quasi-Poisson and Negative Binomial Regression

In this study, it has been aimed to model the numbers of divorce in Turkey between years 20012009 using Generalized Poisson, Quasi-Poisson and Negative Binomial Regression methods. Data set of this study has been based on the data obtained from Turkish Statistical Institute (TUIK). Response variable-the annual rate of divorcehas been categorized into four groups with respect to the length of ex-married life of divorced couples. Explanatory variables have been designated as average age of the first marriage of men and women, the professional work life ratio of married women, the percentage of university graduates in both men and women. For Poisson models, overdispersion parameters have been detected respectively 32.413, 7.277, 16.158 and 26.361. Furthermore Pearson and G statistics have revealed that Poisson models are not appropriate for data set. When Quasi Poisson regression was employed, it has been detected that residual deviances are rather close to Poisson residuals. Finally, Negative binomial regression has been conducted. Overdispersion is a common phenomenon in Poisson modeling. In such data sets certain generalizations of Poisson regression and negative binomial regression modeling are used. In present study negative binomial regression has been detected as approved method.