Abstract
This paper presents first- and second-order statistical models of the total emergency medical service (EMS) demand rate using socio-economic, demographic and other characteristics of an area as the exogenous variables. Due to the multicollinear or non-orthogonal nature of the exogenous data, parameter estimates result are compared with those derived from the ordinary least squares method and a related Bayesian approach. These models are shown to provide highly significant fits to the empirical data. It is suggested that such models possess considerable utility as quantitative tool for evaluating and planning EMS systems.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
