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Transporting stochastic direct and indirect effects to new populations

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  • Kara E. Rudolph
  • Jonathan Levy
  • Mark J. van der Laan

Abstract

Transported mediation effects may contribute to understanding how interventions work differently when applied to new populations. However, we are not aware of any estimators for such effects. Thus, we propose two doubly robust, efficient estimators of transported stochastic (also called randomized interventional) direct and indirect effects. We demonstrate their finite sample properties in a simulation study. We then apply the preferred substitution estimator to longitudinal data from the Moving to Opportunity Study, a large‐scale housing voucher experiment, to transport stochastic indirect effect estimates of voucher receipt in childhood on subsequent risk of mental health or substance use disorder mediated through parental employment across sites, thereby gaining understanding of drivers of the site differences.

Suggested Citation

  • Kara E. Rudolph & Jonathan Levy & Mark J. van der Laan, 2021. "Transporting stochastic direct and indirect effects to new populations," Biometrics, The International Biometric Society, vol. 77(1), pages 197-211, March.
    • Handle: RePEc:bla:biomet:v:77:y:2021:i:1:p:197-211
    DOI: 10.1111/biom.13274
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    References listed on IDEAS

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    1. D Benkeser & M Carone & M J Van Der Laan & P B Gilbert, 2017. "Doubly robust nonparametric inference on the average treatment effect," Biometrika, Biometrika Trust, vol. 104(4), pages 863-880.
    2. Zheng Wenjing & van der Laan Mark, 2017. "Longitudinal Mediation Analysis with Time-varying Mediators and Exposures, with Application to Survival Outcomes," Journal of Causal Inference, De Gruyter, vol. 5(2), pages 1-24, September.
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