Regression Analysis of Count Data
نویسندگان
چکیده
Three nonlinear count models, Poisson R.egression (PR), Negative Binomial Regression (NBR), and Generalized Poisson Regression (GPR) are used for assessing the effects of risk factors on agricultural injuries from farm injury data. A sample of 1,322 respondents who participated in the farm safety/injury baseline survey in nine rural counties in Alabama and Mississippi, aged 18 years and older are considered for analysis. The dispersion parameter estimates and their standard errors for GPR models were consistently smaller than that of NBR models. Estimated dispersion parameters in the NBR and GPR models were positive and significantly different from zero. Estimated goodness-of-fit measures showed that GPR models outperformed the NBR and PR models.
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