Informative Censoring

What is informative censoring? 

Informative censoring refers to a type of censoring that occurs in statistical analysis, particularly in survival analysis or time-to-event studies, where the reason for a data point being censored (i.e., incomplete or missing) is related to the outcome of interest. This means that the censored data provides valuable information about the likelihood of an event occurring. Unlike non-informative censoring, where the censoring is random, informative censoring can lead to biased results if not properly accounted for in the analysis. 

Why is informative censoring important? 

Informative censoring is important to recognize because it can affect the accuracy of study results and lead to biased conclusions if not properly handled. In healthcare research and clinical trials, failing to account for informative censoring can distort the understanding of treatment effects, disease progression, and patient outcomes. Proper statistical methods and techniques are required to address this issue and ensure valid conclusions.