The importance of censoring in competing risks analysis of the subdistribution hazard.

Published in: BMC medical research methodology (2017)

The estimation of the censoring distribution can affect the accuracy and conclusions of a competing risks analysis, so it is important that this issue is considered carefully when analysing time-to-event data in the presence of competing risks.

Keyphrases

human health
risk assessment
deep learning