Penalized regression calibration: A method for the prediction of survival outcomes using complex longitudinal and high‐dimensional data

• Published in: Statistics in medicine Vol. 40; no. 27; pp. 6178 - 6196
• Main Authors: Signorelli, Mirko, Spitali, Pietro, Szigyarto, Cristina Al‐Khalili, Tsonaka, Roula
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 30.11.2021; John Wiley and Sons Inc
• Subjects: Bias; Biomarkers; Calibration; Clinical outcomes; Duchenne muscular dystrophy; high-dimensionality; Humans; longitudinal data analysis; Longitudinal Studies; Medical statistics; optimism correction; penalized regression calibration; Proportional Hazards Models; Regression analysis; risk prediction modeling; Survival analysis; survival analysis; Duchenne muscular dystrophy; penalized regression calibration; longitudinal data analysis; optimism correction; high-dimensionality; risk prediction modeling

Longitudinal and high‐dimensional measurements have become increasingly common in biomedical research. However, methods to predict survival outcomes using covariates that are both longitudinal and high‐dimensional are currently missing. In this article, we propose penalized regression calibration (P...