Chapter Longitudinal profile of a set of biomarkers in predicting Covid-19 mortality using joint models
In survival analysis, time-varying covariates are endogenous when their measurements are directly related to the event status and incomplete information occur at random points during the follow-up. Consequently, the time-dependent Cox model leads to biased estimates. Joint models (JM) allow to corre...
में बचाया:
मुख्य लेखक: | Ferrante, Pasquale (auth) |
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अन्य लेखक: | DI MASO, MATTEO (auth), Ferraroni, Monica (auth), Delbue, Serena (auth), Ambrogi, Federico (auth) |
स्वरूप: | इलेक्ट्रोनिक पुस्तक अध्याय |
भाषा: | अंग्रेज़ी |
प्रकाशित: |
Florence
Firenze University Press
2021
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श्रृंखला: | Proceedings e report
132 |
विषय: | |
ऑनलाइन पहुंच: | OAPEN Library: download the publication OAPEN Library: description of the publication |
टैग: |
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समान संसाधन
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Chapter Longitudinal profile of a set of biomarkers in predicting Covid-19 mortality using joint models
द्वारा: Ferrante, Pasquale
प्रकाशित: (2021) -
Chapter Longitudinal profile of a set of biomarkers in predicting Covid-19 mortality using joint models
द्वारा: Ferrante, Pasquale
प्रकाशित: (2021) -
Chapter Longitudinal profile of a set of biomarkers in predicting Covid-19 mortality using joint models
द्वारा: Ferrante, Pasquale
प्रकाशित: (2021) -
Chapter The joint estimation of accuracy and speed: An application to the INVALSI data
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Chapter The joint estimation of accuracy and speed: An application to the INVALSI data
द्वारा: Bungaro, Luca
प्रकाशित: (2023)