TY - CHAP
T1 - Statistical Methods in Medicine
T2 - Application to the Study of Glaucoma Progression
AU - Guglielmi, Alessandra
AU - Guidoboni, Giovanna
AU - Harris, Alon
AU - Sartori, Ilaria
AU - Torriani, Luca
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85076726323&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-25886-3_24
DO - 10.1007/978-3-030-25886-3_24
M3 - Chapter
AN - SCOPUS:85076726323
T3 - Modeling and Simulation in Science, Engineering and Technology
SP - 599
EP - 612
BT - Modeling and Simulation in Science, Engineering and Technology
PB - Birkhauser
ER -