Transformation models with informative partly interval-censored data

• Published in: Statistics and computing Vol. 34; no. 1
• Main Authors: Jiang, Jingjing, Wang, Chunjie, Pan, Deng, Song, Xinyuan
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2024; Springer Nature B.V
• Subjects: Artificial Intelligence; Bayesian analysis; Censored data (mathematics); Computer Science; Data augmentation; Data structures; Factor analysis; Failure times; Markov chains; Original Paper; Probability and Statistics in Computer Science; Statistical models; Statistical Theory and Methods; Statistics and Computing/Statistics Programs; Stochastic processes; Survival analysis; Latent factor; Data augmentation; Bayesian method; Informative partly-interval censoring; Transformation model

Partly interval censoring is frequently encountered in clinical trials when the failure time of an event is observed exactly for some subjects but is only known to fall within an observed interval for others. Although this kind of censoring has drawn recent attention in survival analysis, available...