2023
Riemannian frameworks for the harmonization of resting-state functional MRI scans
Honnorat N, Seshadri S, Killiany R, Blangero J, Glahn D, Fox P, Habes M. Riemannian frameworks for the harmonization of resting-state functional MRI scans. Medical Image Analysis 2023, 91: 103043. PMID: 38029722, PMCID: PMC11157681, DOI: 10.1016/j.media.2023.103043.Peer-Reviewed Original ResearchRiemannian geometric frameworkHigh-dimensional data setsMathematical propertiesFunctional time seriesTime seriesGeometric frameworkLow-dimensional data setsStatistical methodsCovariate effectsData setsGreater statistical powerSynthetic dataStatistical powerImpact of covariatesLarge setSetABIDE consortiumNew frameworkA Synthetic Data Integration Framework to Leverage External Summary-Level Information from Heterogeneous Populations
Gu T, Taylor J, Mukherjee B. A Synthetic Data Integration Framework to Leverage External Summary-Level Information from Heterogeneous Populations. Biometrics 2023, 79: 3831-3845. PMID: 36876883, PMCID: PMC10480346, DOI: 10.1111/biom.13852.Peer-Reviewed Original ResearchConceptsCovariate effectsStatistical inferenceHeterogeneity of covariate effectsRegression coefficient estimatesSummary-level informationImprove statistical inferenceInternational studiesOutcome YCovariate informationData integration frameworkStatistical efficiencyCoefficient estimatesPartial informationExternal populationGeneral frameworkIndividual-level dataRisk prediction modelExternal modelPrediction problemInternational study populationMultiple imputation
2013
Testing for a Changepoint in the Cox Survival Regression Model
Zucker D, Agami S, Spiegelman D. Testing for a Changepoint in the Cox Survival Regression Model. Journal Of Statistical Theory And Practice 2013, 7: 360-380. DOI: 10.1080/15598608.2013.772030.Peer-Reviewed Original ResearchMaximum efficiency robust testCovariate domainSupremum-type testsTest statisticEfficiency robust testSupremum statisticsFirst author's websiteNurses' Health StudyCox survival regression modelType statisticsPower calculationCovariate effectsAuthor's websiteSimulation studySurvival regression modelsLinear combination formStandard Cox modelBest overall choicePopular modelsSimulation resultsFatal myocardial infarctionCox regression modelMATLAB softwareStatisticsRobust test
2009
Graphical diagnostics to check model misspecification for the proportional odds regression model
Liu I, Mukherjee B, Suesse T, Sparrow D, Park S. Graphical diagnostics to check model misspecification for the proportional odds regression model. Statistics In Medicine 2009, 28: 412-429. PMID: 18693299, DOI: 10.1002/sim.3386.Peer-Reviewed Original ResearchConceptsCovariate effectsOrdinal responsesModel misspecificationProportional odds regression modelStudy covariate effectsGoodness-of-fit statisticsClass of modelsNumerical methodFunctional misspecificationBinary responsesGraphical diagnosticsSimulation studyCumulative logitsMisspecificationCumulative sumRegression modelsGraphical methodSumArbogastVA Normative Aging StudyCovariatesProportional odds regressionClass
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
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