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Misclassification of the mediator matters when estimating indirect effects
  1. Tony Blakely,
  2. Sarah McKenzie,
  3. Kristie Carter
  1. Health Inequalities Research Programme, Department of Public Health, University of Otago Wellington, Wellington, New Zealand
  1. Correspondence to Dr Tony Blakely, Health Inequalities Research Programme, Department of Public Health, University of Otago Wellington, Mein Street, Wellington 6022, New Zealand; tony.blakely{at}otago.ac.nz

Abstract

Background Confounding of mediator–outcome associations resulting in collider biases causes systematic error when estimating direct and indirect effects. However, until recently little attention has been given to the impact of misclassification bias.

Objective To quantify the impact of non-differential and independent misclassification of a dichotomous exposure and a dichotomous mediator on three target parameters: the total effect of exposure on outcome; the direct effect (by conditioning on the mediator); and the indirect effect (identified by the percentage reduction in the excess OR on adjusting for the mediator).

Methods Simulations were conducted for varying strength of associations between exposure, mediator and outcome, varying ratios of exposed to unexposed and mediator present to mediator absent, and varying sensitivity and specificity of exposure and mediator classification.

Results ORs before (total effect) and after adjustment (direct effect) for the mediator are both biased towards the null by non-differential misclassification of the exposure, but the percentage reduction in the excess OR is little affected by misclassification of exposure. Conversely, misclassification of the mediator rapidly biases the percentage reduction of the excess OR (indirect effect) downwards.

Conclusions If the research objective is to quantify the proportion of the total association that is due to mediation (ie, indirect effect), then minimising non-differential misclassification bias of the mediator is more important than that for the exposure. Misclassification bias is an important source of error when estimating direct and indirect effects.

  • Epidemiology
  • Methodology
  • Measurement

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