ArticleStatistics in medicine2018
A Bayesian semiparametric latent variable approach to causal mediation.
Article in Statistics in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Bayesian Nonparametric Model for Heterogeneous Treatment Effects With Zero-Inflated Data.Statistics in medicine · 2024Article
- A Causal Mediation Model for Longitudinal Mediators and Survival Outcomes with an Application to Animal Behavior.Journal of agricultural, biological, and environmental statistics · 2023Article
- CAUSAL MEDIATION ANALYSIS FOR SPARSE AND IRREGULAR LONGITUDINAL DATA.The annals of applied statistics · 2021Article
- A practical introduction to Bayesian estimation of causal effects: Parametric and nonparametric approaches.Statistics in medicine · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
In assessing causal mediation effects in randomized studies, a challenge is that the direct and indirect effects can vary across participants due to different measured and unmeasured characteristics. In that case, the population effect estimated from standard approaches implicitly averages over and does not estimate the heterogeneous direct and indirect effects. We propose a Bayesian semiparametric method to estimate heterogeneous direct and indirect effects via clusters, where the clusters are formed by both individual covariate profiles and individual effects due to unmeasured characteristics. These cluster-specific direct and indirect effects can be estimated through a set of regression models where specific coefficients are clustered by a stick-breaking prior. To let clustering be appropriately informed by individual direct and indirect effects, we specify a data-dependent prior. We conduct simulation studies to assess performance of the proposed method compared to other methods. We use this approach to estimate heterogeneous causal direct and indirect effects of an expressive writing intervention for patients with renal cell carcinoma.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.