Dear All.

Apologies for posting a question regarding survival analysis, and not R, to the 
R-help list. In the past I received the best advices from the R community.


The random censorship model (the censoring times independent of the failure 
times and vice versa) is one of the fundamental assumptions in the survival 
analysis. In the medical studies we have random entry to study and study end 
which is a censoring mechanism independent of the failure times. However, in 
reality we may have dropout subjects, lost to follow-up, which are censored by 
a different mechanism which may not be independent of the failure times. The 
inclusion of dropout subjects in the survival analysis may break the random 
censorship model and include bias in our estimates of survival with KM. I have 
studied papers on this subject (e.g. double sampling, copula approach for 
dependent censoring), but I have not found any research paper which examines 
the removal of dropout subjects from the survival analysis.


I am alone in my research and would be grateful to hear thoughts on this 
subject. Thank you in advance and apologies for using the R-help list for my 
research question.


DK

        [[alternative HTML version deleted]]

______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Reply via email to