Controlling for Large Sets of Measured Confounders in Mediation Analysis
Comparison of Bayesian Model Averaging, the Lasso, and Path Analysis
Bibliographic Data
| ID | 12424923 |
|---|---|
| Authors | Milica Miočević (0000-0001-8487-3666, McGill University, corresponding author), Denis Talbot (0000-0003-0431-3314, Université Laval) |
| Year | 2025 |
| Volume | 33 |
| Issue | 1 |
| Pages | 39-49 |
| Publication date | 2025-10-10 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Structural Equation Modeling: A Multidisciplinary Journal (JOURNAL) |
| Journal identifiers | ISSN: 1070-5511 • E-ISSN: 1532-8007 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/10705511.2025.2559270 |
| OpenAlex | W4415059812 |
| Language | EN |
| References cited | 24 |
Advanced Causal Inference Techniques · Statistical Methods and Bayesian Inference · Statistical Methods in Clinical Trials
Robustness?
Identification, Inference and Sensitivity Analysis for Causal Mediation Effects
The Adaptive Lasso and Its Oracle Properties
Mediation analysis allowing for exposure–mediator interactions and causal interpretation
Causal Inference Using Potential Outcomes
Regression Shrinkage and Selection Via the Lasso
A general approach to causal mediation analysis.
A comparison of methods to test mediation and other intervening variable effects.
Adjusting for Baseline Measurements of the Mediators and Outcome as a First Step Toward Eliminating Confounding Biases in Mediation Analysis
Confidence Limits for the Indirect Effect
| Citation velocity | historical |
|---|---|
| Highly cited | No |