Supplemental Material for Causal Decomposition Analysis With Synergistic Interventions: A Triply Robust Machine-Learning Approach to Addressing Multiple Dimensions of Social Disparities

Equalizing the individual factor while setting the system-level factor to a pre-specified level.The expected potential outcome is defined as. This represents the average potential outcome for individuals with R = 1 and C = c, if the system-level factor is set to A = a while the distribution of the individual factor was equal to that of R = 0 within the same level of C M = c M .This expected potential outcome can also be estimated using a triply-robust estimator.The estimation procedure is similar to that described in Section 4.2, except that factor A is not simulated fromThe triply-robust estimator for the potential outcome (E[Y (a, G M |R=0,C M )|R = 1, C = c]) is as Prepared using sagej.

Publication Details

Journal
Psychological Methods
Published
2025-10-23
DOI
https://doi.org/10.1037/met0000803.supp
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Supplemental Material for Causal Decomposition Analysis With Synergistic Interventions: A Triply Robust Machine-Learning Approach to Addressing Multiple Dimensions of Social Disparities

Psychological Methods
Advanced Causal Inference Techniques
article

Supplemental Material for Causal Decomposition Analysis With Synergistic Interventions: A Triply Robust Machine-Learning Approach to Addressing Multiple Dimensions of Social Disparities

article en

Abstract

Equalizing the individual factor while setting the system-level factor to a pre-specified level.The expected potential outcome is defined as. This represents the average potential outcome for individuals with R = 1 and C = c, if the system-level factor is set to A = a while the distribution of the individual factor was equal to that of R = 0 within the same level of C M = c M .This expected potential outcome can also be estimated using a triply-robust estimator.The estimation procedure is similar to that described in Section 4.2, except that factor A is not simulated fromThe triply-robust estimator for the potential outcome (E[Y (a, G M |R=0,C M )|R = 1, C = c]) is as Prepared using sagej.

Psychological Methods
Openalex Percentile: Top 72%
Advanced Causal Inference Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.