What occurs in a time-to-event analysis when an event has not occurred for a subject?

In time-to-event analysis, when an event has not occurred for a subject, it is appropriate to set the time-to-event variable to the last follow-up day. This approach is foundational in survival analysis, where the goal is to estimate the time until an event happens, such as the onset of a disease or a system failure.

In instances where a subject has not experienced the event during the study period (for example, they might have been lost to follow-up or simply have not yet experienced the event), their last known data point becomes crucial. Documenting the last follow-up day allows researchers to include this subject's information in the analysis without falsely representing the outcome.

This practice addresses censoring, which occurs when we know that the event of interest has not occurred by the end of the study or the last contact with the subject. Correctly accounting for censored data ensures that the analysis remains valid and the results are representative of the population under study.

As for the other options, they would not accurately represent the situation for subjects who have not experienced the event by the end of the follow-up period. Setting the variable to the event day would be misleading, excluding the subject would reduce the sample size unnecessarily, and recording the event as a success would inaccur