2008
Semiparametric Bayesian modeling of random genetic effects in family‐based association studies
Zhang L, Mukherjee B, Hu B, Moreno V, Cooney K. Semiparametric Bayesian modeling of random genetic effects in family‐based association studies. Statistics In Medicine 2008, 28: 113-139. PMID: 18792083, PMCID: PMC2684653, DOI: 10.1002/sim.3413.Peer-Reviewed Original ResearchConceptsRandom effects distributionRandom effects parametersBayesian approachProblem of estimating covarianceSensitive to parametric specificationSemiparametric Bayesian modelNonparametric Bayesian approachFixed covariate effectsFlexible Bayesian approachEffective distributionIntegrated likelihoodDirichlet processCovariate effectsNonparametric modelBayesian paradigmParametric specificationHierarchical Bayesian paradigmBayes methodologyInference problemSimulation studyRandom genetic effectsComputational advantagesCorrelation structureNumerical integration schemeTheoretical sense
2007
Semiparametric Bayesian Analysis of Case–Control Data under Conditional Gene-Environment Independence
Mukherjee B, Zhang L, Ghosh M, Sinha S. Semiparametric Bayesian Analysis of Case–Control Data under Conditional Gene-Environment Independence. Biometrics 2007, 63: 834-844. PMID: 17489972, DOI: 10.1111/j.1541-0420.2007.00750.x.Peer-Reviewed Original ResearchConceptsGene-environment independenceSemiparametric Bayesian approachTraditional logistic regression analysisParametric model assumptionsSemiparametric Bayesian modelCase-control studyPopulation-based case-control studySimulation studyBayesian approachRobust alternativeLogistic regression analysisUnderlying populationEfficient estimation techniqueBayesian modelEnvironmental exposuresModel assumptionsScientific evidenceRegression analysisAssociated with diseaseEstimation techniquesOvarian cancerControl populationPopulationIndependenceCovariates