2012
A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies
Bhadra D, Daniels M, Kim S, Ghosh M, Mukherjee B. A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies. Biometrics 2012, 68: 361-370. PMID: 22313248, PMCID: PMC3935236, DOI: 10.1111/j.1541-0420.2011.01686.x.Peer-Reviewed Original ResearchConceptsBayesian semiparametric approachSemiparametric approachCase-control studyReversible jump Markov chain Monte Carlo algorithmMarkov chain Monte Carlo algorithmMeasures of cumulative exposureLongitudinal biomarker informationMonte Carlo algorithmClinically meaningful estimatesSmooth functionsCase-control study of prostate cancerWeighted integralsCumulative exposureInfluence functionJoint likelihoodLikelihood formulationExposure historyStudy of prostate cancerDisease risk modelsHierarchical Bayesian frameworkDisease statusBayesian frameworkCase-controlRisk modelCohort study
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