Limitation of inverse probability-of-censoring weights in estimating survival in the presence of strong selection bias.

ABSTRACT: In time-to-event analyses, artificial censoring with correction for induced selection bias using inverse probability-of-censoring weights can be used to 1) examine the natural history of a disease after effective interventions are widely available, 2) correct bias due to noncompliance with fixed or dynamic treatment regimens, and 3) estimate survival in the presence of competing risks. Artificial censoring entails censoring participants when they meet a predefined study criterion, such as exposure to an intervention, failure to comply, or the occurrence of a competing outcome. Inverse probability-of-censoring weights use measured common predictors of the artificial censoring mechanism and the outcome of interest to determine what the survival experience of the artificially censored partici

SUBMITTER: Howe CJ 

PROVIDER: S-EPMC3105434 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature