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Misclassification of the mediator matters when estimating indirect effects
Tony Blakely1, Sarah McKenzie, Kristie Carter
1Health Inequalities Research Programme, Department of Public Health, University of Otago Wellington, Mein Street, Wellington, New Zealand. tony.blakely@otago.ac.nz
Misclassification bias significantly impacts estimations of direct and indirect effects. Minimizing mediator misclassification is crucial for accurately quantifying the indirect effect, more so than exposure misclassification.
Area of Science:
- Epidemiology
- Biostatistics
Background:
- Collider bias can cause systematic errors in estimating direct and indirect effects.
- Misclassification bias has a significant, yet underappreciated, impact on these estimations.
Purpose of the Study:
- To quantify the impact of misclassification bias on total, direct, and indirect effects.
- To assess the influence of dichotomous exposure and mediator misclassification.
Main Methods:
- Conducted simulations with varying exposure-mediator-outcome associations.
- Varied ratios of exposed/unexposed and mediator presence/absence.
- Simulated varying sensitivity and specificity for exposure and mediator classification.
Main Results:
- Non-differential exposure misclassification biases total and direct effects towards the null.
- Exposure misclassification minimally affects the percentage reduction in excess odds ratio (indirect effect).
- Mediator misclassification significantly biases the indirect effect downwards.
Conclusions:
- Minimizing mediator misclassification is critical for accurately estimating the indirect effect.
- Misclassification bias is a substantial source of error in direct and indirect effect estimation.
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