971 resultados para Computer Modeling


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Magdeburg, Univ., Fak. für Informatik, Diss., 2013

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2013

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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2013

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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2013

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Magdeburg, Univ., Fak. für Informatik, Diss., 2014

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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2014

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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2014

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Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2015

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Magdeburg, Univ., Fak. für Informatik, Diss., 2015

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2015

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Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Univ., Dissertation, 2015

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We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favored, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required.

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We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.