Modelling Motorcycle-Related Head Injury Trends for Thailand Following the 100% Motorcycle Helmet Use Campaign Using
Keywords:Poisson log-linear model, negative binomial log-linear model, count data
The aim of this paper is to examine trends of motorcycle related head injuries in HRH Princess Maha Chakri Sirindhorn Medical Center, Nakhon Nayok province, Thailand, following the 100% Motorcycle Helmet Use campaign by using log-linear models. Since the injuries count data is overdispersion, the Poisson log-linear model is not reasonable. Consequently, the negative binomial log-linear model accounted for overdispersion is used, and it fits the data very well. The fitted model indicated the increasing trend of head injuries after the 100% Motorcycle Helmet Use campaign was lunched over the years 2011-2016. It is increasing at the rate 1.13% per month.
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