Informative Censoring-A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data

• Published in: Life (Basel, Switzerland) Vol. 13; no. 1; p. 210
• Main Authors: Lin, Hung-Mo, Liu, Sean T H, Levin, Matthew A, Williamson, John, Bouvier, Nicole M, Aberg, Judith A, Reich, David, Egorova, Natalia
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.01.2023; MDPI
• Subjects: Analysis; Bias; Bias (Statistics); censoring; Censoring (Statistics); convalescent plasma; Coronaviruses; COVID-19; Electronic data processing; Hospital care; Medical research; Medicine, Experimental; Methods; Mortality; Patient outcomes; Statistical models; Statistics; United States; United States; United States > US; New York City New York; COVID-19; censoring; convalescent plasma

(1) Background: Several retrospective observational analyzed treatment outcomes for COVID-19; (2) Methods: Inverse probability of censoring weighting (IPCW) was applied to correct for bias due to informative censoring in database of hospitalized patients who did and did not receive convalescent plas...