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
Accounting for error due to misclassification of exposures in case–control studies of gene–environment interaction
Zhang L, Mukherjee B, Ghosh M, Gruber S, Moreno V. Accounting for error due to misclassification of exposures in case–control studies of gene–environment interaction. Statistics In Medicine 2007, 27: 2756-2783. PMID: 17879261, DOI: 10.1002/sim.3044.Peer-Reviewed Original ResearchConceptsCase-control studyCase-control study of colorectal cancerGene-environment independence assumptionStudy of gene-environment interactionsStudy of colorectal cancerCase-control study designEnvironmental exposuresDisease-exposure associationsCase-control dataMisclassification of exposureGene-environment interactionsDegree of misclassificationStudy designConfidence intervalsGenotyping errorsValidation subsampleColorectal cancerAnalysis of dataMisclassification error rateGenetic factorsIndependence assumptionMisclassificationMisclassified dataAnalytical formEstimation strategy