A Latent Variable Approach to Study Gene-Environment Interactions in the Presence of Multiple Correlated Exposures

DOI10.1111/J.1541-0420.2011.01677.XzbMath1274.62867OpenAlexW2052466581WikidataQ35519919 ScholiaQ35519919MaRDI QIDQ2912342

Bhramar Mukherjee, Shan Kang, Brisa N. Sánchez

Publication date: 14 September 2012

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4405908

zbMATH Keywords

shrinkage estimationprincipal componentsstructural equation modelsgene-environment independence

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Genetics and epigenetics (92D10)

Related Items (2)

Effects of gene-environment and gene-gene interactions in case-control studies: a novel Bayesian semiparametric approach ⋮ Using a latent variable model with non-constant factor loadings to examine PM_2.5 constituents related to secondary inorganic aerosols

Cites Work

• Unnamed Item
• Unnamed Item
• Joint modelling of multivariate longitudinal outcomes and a time-to-event: a nonlinear latent class approach
• Building an identifiable latent class model with covariate effects on underlying and measured variables
• Exploiting Gene‐Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes‐Type Shrinkage Estimator to Trade‐Off between Bias and Efficiency
• Frequentist Model Average Estimators
• Latent Variable Models for Longitudinal Data with Multiple Continuous Outcomes
• Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies
• Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies
• Structural Equation Models
• Assessing Interaction Effects in Linear Measurement Error Models

This page was built for publication: A Latent Variable Approach to Study Gene-Environment Interactions in the Presence of Multiple Correlated Exposures