A Python library for moderation, mediation and conditional process analysis.
Causing: CAUsal INterpretation using Graphs
R implementation of effect measure modification-extended regression-based closed-formula causal mediation analysis
Fast regression and mediation analysis of vertex or voxel MRI data with TFCE
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
Plain-language guide to causal inference for microbiome & multi-omics: DAGs/backdoor, confounders vs mediators/colliders, causal mediation (ACME/ADE/Total), and Double Machine Learning (DML) with toy examples + code.
📦 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
R research code for debiased causal mediation in ultra-high-dimensional settings with interaction effects.
📦 🎲 R/medshift: Causal Mediation Analysis for Stochastic Interventions
问卷/量表数据��析全流程方法学 Skill（中英文通用）：信效度·EFA/CFA·SEM·中介调节·APA报告 + 离线阈值速查表（SPSS/AMOS/R）
R package to conduct mediation analysis using joint significance.
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
The Simplest and Most Correct Way to Do Causal Mediation Analysis
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
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