ArticleGenetic epidemiology2020
Penalized models for analysis of multiple mediators.
Article in Genetic epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Integrated analysis of the diabetic foot ulcer microbiome and host transcriptome supports a microenvironment-microbiota-host repair framework.Endocrine · 2026Article
- Cariogenic microorganisms induce oral epithelial atypia through host-microbiome-high sugar diet interactions.NPJ biofilms and microbiomes · 2026Article
- The interplay of sleep characteristics with health factors and gut microbiome.Nature communications · 2026Article
- Causal mediation analysis: selection with asymptotically valid inference.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2025Article
- Collider bias correction for multiple covariates in GWAS using robust multivariable Mendelian randomization.PLoS genetics · 2024Article
- Model Selection for Exposure-Mediator Interaction.Data science in science · 2024Article
- Penalized mediation models for multivariate data.Genetic epidemiology · 2022Article
- Heterogeneous Mediation Analysis on Epigenomic PTSD and Traumatic Stress in a Predominantly African American Cohort.Journal of the American Statistical Association · 2022Article
- Associations between indicators of socioeconomic position and DNA methylation: a scoping review.Clinical epigenetics · 2021Article
- Transcriptional signatures associated with rubella virus-specific humoral immunity after a third dose of MMR vaccine in women of childbearing age.European journal of immunology · 2021Article
- Statistical methods for mediation analysis in the era of high-throughput genomics: Current successes and future challenges.Computational and structural biotechnology journal · 2021Review
- Inferring causal direction between two traits in the presence of horizontal pleiotropy with GWAS summary data.PLoS genetics · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Mediation analysis attempts to determine whether the relationship between an independent variable (e.g., exposure) and an outcome variable can be explained, at least partially, by an intermediate variable, called a mediator. Most methods for mediation analysis focus on one mediator at a time, although multiple mediators can be jointly analyzed by structural equation models (SEMs) that account for correlations among the mediators. We extend the use of SEMs for the analysis of multiple mediators by creating a sparse group lasso penalized model such that the penalty considers the natural groupings of parameters that determine mediation, as well as encourages sparseness of the model parameters. This provides a way to simultaneously evaluate many mediators and select those that have the most impact, a feature of modern penalized models. Simulations are used to illustrate the benefits and limitations of our approach, and application to a study of DNA methylation and reactive cortisol stress following childhood trauma discovered two novel methylation loci that mediate the association of childhood trauma scores with reactive cortisol stress levels. Our new methods are incorporated into R software called regmed.
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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.