2010
Missing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification
Ahn J, Mukherjee B, Gruber S, Sinha S. Missing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification. Biometrics 2010, 67: 546-558. PMID: 20560931, PMCID: PMC3119773, DOI: 10.1111/j.1541-0420.2010.01453.x.Peer-Reviewed Original ResearchConceptsStereotype regression modelSubtypes of casesDeletion of observationsExpectation/conditional maximization algorithmBaseline category logit modelEstimation of model parametersMissingness mechanismData mechanismCase-control dataProportional oddsBayesian approachCategorical responsesCase-control studyCase-control study of colorectal cancerMissingnessMaximization algorithmCategorical outcomesMonte CarloModel assumptionsRegression modelsStudy of colorectal cancerModel parametersNonidentifiabilityDisease subclassificationMultinomial logit model
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