What question did this study set out to answer?

To explore the impact of smoking on cognition and attrition bias in longitudinal studies using a joint model approach.

April 25, 2026American Journal of Epidemiology1 citations

Smoking hot joint models for attrition bias—XMAR-ks the spot

MGMichael E Griswold RVRavi VaradhanJohns Hopkins University

Key Points

To explore the impact of smoking on cognition and attrition bias in longitudinal studies using a joint model approach.
Compared standard linear mixed model to a joint model approach.
Examined extended missing at random (XMAR) assumption within a four-level missingness taxonomy.
Conducted sequential sensitivity analysis with data on smoking and cognitive decline.
Joint model showed improved handling of attrition bias compared to standard model.
Sequential analysis illustrated significant cognitive decline associated with smoking, particularly in cases of dementia and death.
Highlighted need for robust methods to address informative censoring in longitudinal studies.

Abstract

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.

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