ArticleJournal of exposure science & environmental epidemiology2012
A Bayesian mixture modeling approach for assessing the effects of correlated exposures in case-control studies.
Article in Journal of exposure science & environmental epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Discovery of critical thresholds in mixed exposures and estimation of policy intervention effects.Journal of causal inference · 2026Article
- Application of Toxicologically Informed Relative Potency Factors to Examine Associations between Water Disinfection Byproducts and Birth Defects.Environmental science & technology · 2025Article
- Advancing environmental epidemiologic methods to confront the cancer burden.American journal of epidemiology · 2025Article
- Bayesian Group Index Regression for Modeling Chemical Mixtures and Cancer Risk.International journal of environmental research and public health · 2021Article
- Assessing the Relation between Plasma PCB Concentrations and Elevated Autistic Behaviours using Bayesian Predictive Odds Ratios.International journal of environmental research and public health · 2019Article
- Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures.Biostatistics (Oxford, England) · 2018Article
- A multivariate approach to investigate the combined biological effects of multiple exposures.Journal of epidemiology and community health · 2018Article
- Assessment of Offspring DNA Methylation across the Lifecourse Associated with Prenatal Maternal Smoking Using Bayesian Mixture Modelling.International journal of environmental research and public health · 2015Article
- Air toxics and birth defects: a Bayesian hierarchical approach to evaluate multiple pollutants and spina bifida.Environmental health : a global access science source · 2015Article
- Effects of non-differential exposure misclassification on false conclusions in hypothesis-generating studies.International journal of environmental research and public health · 2014Article
- The association between different night shiftwork factors and breast cancer: a case-control study.British journal of cancer · 2013Article
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Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predisposition to a disease is usually caused by cumulative effects of a multitude of exposures and lifestyle factors in combination with individual susceptibility. Failure to include all relevant variables may result in biased risk estimates and decreased power, whereas inclusion of all variables may lead to computational difficulties, especially when variables are correlated. We describe a Bayesian Mixture Model (BMM) incorporating a variable-selection prior and compared its performance with logistic multiple regression model (LM) in simulated case-control data with up to twenty exposures with varying prevalences and correlations. In addition, as a practical example we re analyzed data on male infertility and occupational exposures (Chaps-UK). BMM mean-squared errors (MSE) were smaller than of the LM, and were independent of the number of model parameters. BMM type I errors were minimal (≤1), whereas for the LM this increased with the number of parameters and correlation between exposures. The numbers of type II errors were comparable. Re analysis of Chaps-UK data demonstrated more convincingly than by using a LM that occupational exposure to glycol ethers and VOCs are likely risk factors for male infertility. This BMM proves an appealing alternative to standard logistic regression when dealing with the analysis of (correlated) exposures in case-control studies.
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