Statistical Methods in Medicine: Application to the Study of Glaucoma Progression

Alessandra Guglielmi, Giovanna Guidoboni, Alon Harris, Ilaria Sartori, Luca Torriani

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish (US)
Title of host publicationModeling and Simulation in Science, Engineering and Technology
PublisherBirkhauser
Pages599-612
Number of pages14
DOIs
StatePublished - Jan 1 2019
Externally publishedYes

Publication series

NameModeling and Simulation in Science, Engineering and Technology
ISSN (Print)2164-3679
ISSN (Electronic)2164-3725

ASJC Scopus subject areas

  • Modeling and Simulation
  • Engineering(all)
  • Fluid Flow and Transfer Processes
  • Computational Mathematics

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  • Cite this

    Guglielmi, A., Guidoboni, G., Harris, A., Sartori, I., & Torriani, L. (2019). Statistical Methods in Medicine: Application to the Study of Glaucoma Progression. In Modeling and Simulation in Science, Engineering and Technology (pp. 599-612). (Modeling and Simulation in Science, Engineering and Technology). Birkhauser. https://doi.org/10.1007/978-3-030-25886-3_24