We analyze data collected as an observational study by Sacco Hospital patients diagnosed with COVID-19 from the start of the pandemic in early 2020 through December 2022. The list of long-term COVID-19 symptoms includes, among others, fatigue, breathing trouble, rapid heart rhythms, difficulty thinking or concentrating. We analyzed the joint association of the symptoms with the chance of recovering and the effects of covariates through the hidden Markov model for multivariate continuous longitudinal responses that accounts for partially missing outcomes at a given time occasion and dropout.
Pennoni, F., Bartolucci, F., Spinelli, D., Vittadini, G. (2023). Analysis of Sacco Hospital longitudinal data by hidden Markov models. Intervento presentato a: Workshop intermedio Progetto: Analisi causale delle determinanti dello stato di salute dei pazienti affetti da “long-Covid” sulla base di dati clinici, funzionali e strumentali: uno studio longitudinale multicentro, Dipartimento di Economia Perugia.
Analysis of Sacco Hospital longitudinal data by hidden Markov models
Pennoni, F;Spinelli, D;Vittadini, G
2023
Abstract
We analyze data collected as an observational study by Sacco Hospital patients diagnosed with COVID-19 from the start of the pandemic in early 2020 through December 2022. The list of long-term COVID-19 symptoms includes, among others, fatigue, breathing trouble, rapid heart rhythms, difficulty thinking or concentrating. We analyzed the joint association of the symptoms with the chance of recovering and the effects of covariates through the hidden Markov model for multivariate continuous longitudinal responses that accounts for partially missing outcomes at a given time occasion and dropout.
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