It's been said that smoking is a leading cause of statistics. Striving to understand relationships between smoking, cognition, dementia and death has long served as a prototypical example of selection bias issues when studying longitudinal change in the presence of likely informative censoring events. The article by Stuckwisch et al. (Am J Epidemiol. 2025: https://doi.org/10.1093/aje/kwaf107) compares results between a standard linear mixed model and an increasingly used Joint Model approach to investigate this long-vexing problem. We describe the nature of the "extended missing at random" (XMAR) assumption of the Joint Model, position the XMAR assumption in an expanded four-level missingness taxonomy, and illustrate a sequential sensitivity analysis using example data on smoking and cognitive decline with attrition by dementia and death events to illuminate approaches.
Griswold et al. (Fri,) studied this question.