A Python library for moderation, mediation and conditional process analysis.

Causing: CAUsal INterpretation using Graphs

Fast regression and mediation analysis of vertex or voxel MRI data with TFCE

R implementation of effect measure modification-extended regression-based closed-formula causal mediation analysis

Flexible mediation analysis using natural effect models in R

The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis

📦 R/medoutcon: Efficient Causal Mediation Analysis with Natural and Interventional Direct/Indirect Effects

R/medltmle: Estimation and Inference for Natural Mediation Effect in Longitudinal Data

MR project investigating the mediating role of mammographic density in the childhood body size and breast cancer relationship

jamovi Advanced Mediation Models

small R utility for mediation analysis

Causal Mediation analysis

📦 🎲 R/medshift: Causal Mediation Analysis for Stochastic Interventions

R package to conduct mediation analysis using joint significance.

Implementations of "Testing individual mediation effects using the logic of Boolean matrix" (JASA 2022) and "Sequential pathway inference for multimodal neuroimaging analysis" (STAT 2022) in Python

This R package is based on the work presented in A. Jérolon et al., "Causal mediation analysis in presence of multiple mediators uncausally related".The work allowing multiple mediation analyzes with a survival outcome was largely developed with Arce Domingo. This work is presented in Domingo-Relloso et al., "Causal mediation for uncausally relate

🎯 🔀 Targeted Learning for Causal Mediation Analysis

A novel meta-analysis framework of the R-squared (R2)-based mediation effect estimation for high-dimensional omics mediators

R package that provides functions to perform and interpret marginal mediation analysis.

Source files for reproducing results reported in the manuscript "Nonparametric Causal Mediation Analysis for Stochastic Interventional (In)Direct Effects" (N.S. Hejazi, K.E. Rudolph, M.J. van der Laan, I. Díaz, Biostatistics, 2022)