An effective methodology for dealing with data extracted from clinical surveys on heart failure linked to the Public Health Database is proposed. A model for recurrent events is used for modelling the occurrence of hospital readmissions in time, thus deriving a suitable way to compute individual cumulative hazard functions. Estimated cumulative hazard trajectories are then treated as functional data, and they are used as covariates along with clinical survey data within the framework of generalized linear models with functional covariates.

Outcome Prediction for Heart Failure Telemonitoring Via Generalized Linear Models with Functional Covariates / S. Baraldo, F. Ieva, A.M. Paganoni, V. Vitelli. - In: SCANDINAVIAN JOURNAL OF STATISTICS. - ISSN 0303-6898. - 40:3(2013 Sep), pp. 403-416. [10.1111/j.1467-9469.2012.00818.x]

Outcome Prediction for Heart Failure Telemonitoring Via Generalized Linear Models with Functional Covariates

F. Ieva
Secondo
;
2013

Abstract

An effective methodology for dealing with data extracted from clinical surveys on heart failure linked to the Public Health Database is proposed. A model for recurrent events is used for modelling the occurrence of hospital readmissions in time, thus deriving a suitable way to compute individual cumulative hazard functions. Estimated cumulative hazard trajectories are then treated as functional data, and they are used as covariates along with clinical survey data within the framework of generalized linear models with functional covariates.
functional data analysis ; generalized linear models ; Public Health Database ; recurrent events processes
Settore SECS-S/01 - Statistica
Settore MAT/06 - Probabilita' e Statistica Matematica
Settore MED/01 - Statistica Medica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/233393
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