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Causal mediation for uncausally related mediators in the context of survival analysis.

Arce Domingo-RellosoAllan JerolonMaria Tellez-PlazaJose D Bermudez
Published in: medRxiv : the preprint server for health sciences (2024)
Using simulations, we demonstrated that our algorithm performs better than the product of coefficients method, even for uncorrelated mediators. The additive hazards model quantifies the effects as rate differences, which constitute a measure of impact, with applications that can be highly informative for public health. Our algorithm can be found in the R package multimediate, which is available in Github.
Keyphrases
  • public health
  • machine learning
  • deep learning
  • neural network
  • molecular dynamics
  • social support
  • depressive symptoms
  • global health
  • monte carlo