Statistical models provide a variety of powerful methods for data analysis in medicine. In this chapter, we aim at illustrating the insights that statistical models can provide regarding the study of disease progression. In particular, we analyze a unique dataset on glaucoma progression by means of mixed-effects statistical models, where the form of the probability distribution for the multiple measurements is assumed to be the same for each individual in the study, but the parameters of that distribution can vary over individuals. Two illustrative case studies are presented in the context of structural and functional progression in glaucoma.

Statistical methods in medicine: application to the study of glaucoma progression

A. Guglielmi;G. Guidoboni;A. Harris;
2019

Abstract

Statistical models provide a variety of powerful methods for data analysis in medicine. In this chapter, we aim at illustrating the insights that statistical models can provide regarding the study of disease progression. In particular, we analyze a unique dataset on glaucoma progression by means of mixed-effects statistical models, where the form of the probability distribution for the multiple measurements is assumed to be the same for each individual in the study, but the parameters of that distribution can vary over individuals. Two illustrative case studies are presented in the context of structural and functional progression in glaucoma.
Ocular Fluid Dynamics: Anatomy, Physiology, Imaging Techniques, and Mathematical Modeling
978-3-030-25885-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1126799
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