A Simulation Platform for Quantifying Survival Bias: An Application to Research on Determinants of Cognitive Decline

Research output: Contribution to journalJournal articlepeer-review

  • Elizabeth Rose Mayeda
  • Eric J Tchetgen Tchetgen
  • Melinda C Power
  • Jennifer Weuve
  • Hélène Jacqmin-Gadda
  • Jessica R Marden
  • Eric Vittinghoff
  • Niels Keiding
  • M Maria Glymour

Bias due to selective mortality is a potential concern in many studies and is especially relevant in cognitive aging research because cognitive impairment strongly predicts subsequent mortality. Biased estimation of the effect of an exposure on rate of cognitive decline can occur when mortality is a common effect of exposure and an unmeasured determinant of cognitive decline and in similar settings. This potential is often represented as collider-stratification bias in directed acyclic graphs, but it is difficult to anticipate the magnitude of bias. In this paper, we present a flexible simulation platform with which to quantify the expected bias in longitudinal studies of determinants of cognitive decline. We evaluated potential survival bias in naive analyses under several selective survival scenarios, assuming that exposure had no effect on cognitive decline for anyone in the population. Compared with the situation with no collider bias, the magnitude of bias was higher when exposure and an unmeasured determinant of cognitive decline interacted on the hazard ratio scale to influence mortality or when both exposure and rate of cognitive decline influenced mortality. Bias was, as expected, larger in high-mortality situations. This simulation platform provides a flexible tool for evaluating biases in studies with high mortality, as is common in cognitive aging research.

Original languageEnglish
JournalAmerican Journal of Epidemiology
Volume184
Issue number5
Pages (from-to)378-87
Number of pages10
ISSN0002-9262
DOIs
Publication statusPublished - 1 Sep 2016

    Research areas

  • Journal Article

ID: 165752634