Two Pitfalls in Survival Analyses of Time-Dependent Exposure: A Case Study in a Cohort of Oscar Nominees

Wolkewitz, Allignol, Schumacher and Beyersmann have a new paper in The American Statistican. This uses data on the survival outcomes of Oscar nominees as a nice illustrative example of the possibility of length bias and time dependent bias in survival analysis problems. This was originally considered by Redelmeier and Singh in an Annals of Internal Medicine paper where it is was claimed that winning an Oscar significantly increased survival prospects. Possible pitfalls of such an analysis could be assuming everyone is at risk of death from birth rather than when they enter the study (e.g. at nomination), assuming people who win an Oscar have the hazard relating to the win from the time of first nomination rather than the time they actually won, and so forth. The authors show the correct model, as well as a series of possible incorrect models, in terms of multi-state models.