The Causal Mediation Formula - A Guide to the Assessment of Pathways and Mechanisms

Abstract

Recent advances in causal inference have given rise to a general and easy-to-use for- mula for assessing the extent to which the effect of one variable on another is mediated by a third. This Mediation Formula is applicable to nonlinear models with both dis- crete and continuous variables, and permits the evaluation of path-specific effects with minimal assumptions regarding the data-generating process. We demonstrate the use of the Mediation Formula in simple examples and illustrate why parametric methods of analysis yield distorted results, even when parameters are known precisely. We stress the importance of distinguishing between the necessary and sufficient interpretations of "mediated-effect" and show how to estimate the two components in nonlinear systems with continuous and categorical variables.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2011
Accession Number
ADA557663

Entities

People

  • Judea Pearl

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Clinical Trials
  • Computer Science
  • Data Analysis
  • Data Science
  • Information Science
  • Linear Systems
  • Mediation
  • Network Science
  • New York
  • Nonlinear Dynamics
  • Nonlinear Systems
  • Psychology
  • Regression Analysis
  • Social Psychology
  • Social Sciences
  • Statistics

Readers

  • Calculus or Mathematical Analysis
  • Database Systems and Applications
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference