2024
A model-free variable screening method for optimal treatment regimes with high-dimensional survival data
Yang C, Cheng Y. A model-free variable screening method for optimal treatment regimes with high-dimensional survival data. Biometrika 2024, 111: 1369-1386. DOI: 10.1093/biomet/asae022.Peer-Reviewed Original ResearchHigh-dimensional survival dataOptimal treatment regimeVariable screening methodClassification problemOutcome-dependent samplingLevel of robustnessSurvival dataNonparametric learning methodKolmogorov-Smirnov approachCensoring distributionTheoretical propertiesModel misspecificationMisclassification error rateLogit lossHinge lossSimulation studyOptimal classifierBinary classificationSelection probabilityLearning methodsError rateRandom forestLung cancer datasetModel assumptionsCancer datasets
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
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