Virtual Reality zur Untersuchung neuronaler Prozesse : Entwicklung und Validierung einer adaptiven Hirn-Computer-Schnittstelle zur dynamischen Interaktion mit Virtual Reality Paradigmen

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

Computer-aided detection of cerebral aneurysms in angiographies

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

Mathematical modeling and evolution of signal transduction pathways and networks

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

Modeling the inelastic behavior of heat exchangers accounting for fluid-structure interactions

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

Modeling of micro- and nanostructures made of films and crystals/fibers arrays

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

Computer-assisted motion compensation and analysis of perfusion ultrasound data

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

Micro scale modeling grain boundary damage under creep conditions

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

Design, modeling and control of an autonomous field robot for white asparagus harvesting

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

Population balance modeling of influenza A virus replication in MDCK cells during vaccine production

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

Towards effective research-paper recommender systems and user modeling based on mind maps

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

Kernspintomographische Untersuchung zur Bedeutung von Rückmeldungen in der Mensch-Computer-Interaktion

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

Dynamics in growth and metabolism of adherent MDCK cells unraveled by an integrated modeling approach

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

Modeling usage of medical care services: the medical expenditure panel survey data, 1996-2000

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.

Likelihood-based approaches to modeling demand for medical care

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.