2024
How to achieve model-robust inference in stepped wedge trials with model-based methods?
Wang B, Wang X, Li F. How to achieve model-robust inference in stepped wedge trials with model-based methods? Biometrics 2024, 80: ujae123. PMID: 39499239, PMCID: PMC11536888, DOI: 10.1093/biomtc/ujae123.Peer-Reviewed Original ResearchConceptsTreatment effect estimandsWorking correlation structureSandwich variance estimatorExchangeable working correlation structureFunction of calendar timeEffect estimandsVariance estimationLink functionStepped wedge trialEstimandsTheoretical resultsCorrelation structureWedge trialsEstimating EquationsCluster randomized trialG-computationLinear mixed modelsInferencePotential outcomesMisspecificationEstimationEffective structureModel-based methodsGeneralized Estimating EquationsMixed modelsBi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise
Cheng X, Landa B. Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise. Information And Inference A Journal Of The IMA 2024, 13: iaae026. PMID: 39309272, PMCID: PMC11415053, DOI: 10.1093/imaiai/iaae026.Peer-Reviewed Original ResearchMatrix scaling problemSinkhorn-KnoppGraph Laplacian operatorGraph-based data analysisManifold dataText]-dimensionalLog factorLaplacian operatorInner productHigh-dimensional spaceConvergence rateGraph LaplacianNumerical experimentsAlternative normalizationNoise vectorGraphApproximate onesOutlier noiseTheoretical resultsConsistency rateData vectorsSK-iterationsKernel bandwidthConvergenceScale problemsOptimal and Safe Estimation for High-Dimensional Semi-Supervised Learning
Deng S, Ning Y, Zhao J, Zhang H. Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning. Journal Of The American Statistical Association 2024, 119: 2748-2759. PMID: 40078670, PMCID: PMC11902906, DOI: 10.1080/01621459.2023.2277409.Peer-Reviewed Original ResearchSemi-supervised estimatorConditional mean functionMean functionSupervised estimationParameters of linear modelsSemi-supervised learningRegression parametersEstimation problemLinear modelSupplementary materialsTheoretical resultsParameter estimationSemi-supervised settingUnlabeled dataLabeled dataEstimationMinimaxMisspecificationNumerical simulationsDataFunctionLearningProblemData analysis
2022
Online Algorithms for Matching Platforms with Multi-Channel Traffic
Manshadi V, Rodilitz S, Saban D, Suresh A. Online Algorithms for Matching Platforms with Multi-Channel Traffic. 2022, 986-987. DOI: 10.1145/3490486.3538326.Peer-Reviewed Original ResearchExternal trafficOnline algorithmTwo-sided platformsRecommendation algorithmCompetitive ratioWebsite trafficPerformance of ACInternational trafficMatching platformTrafficStrong performanceRecommendation enginePseudo-rewardsPlatform problemsStochastic rewardsPath-basedCase studyTargeting opportunitiesMulti-channelAlgorithmOnline matchingOpportunitiesExternal linksTheoretical resultsNonprofits
2020
Leveraging effect size distributions to improve polygenic risk scores derived from summary statistics of genome-wide association studies
Song S, Jiang W, Hou L, Zhao H. Leveraging effect size distributions to improve polygenic risk scores derived from summary statistics of genome-wide association studies. PLOS Computational Biology 2020, 16: e1007565. PMID: 32045423, PMCID: PMC7039528, DOI: 10.1371/journal.pcbi.1007565.Peer-Reviewed Original ResearchConceptsEffect size distributionClass of methodsReal data applicationOnly summary statisticsTheoretical resultsSummary statisticsExtensive simulation resultsLD informationSimulation resultsData applicationsFirst methodImportant problemOptimal propertiesGenetic risk predictionAccurate predictionPrediction accuracyStandard PRSStatisticsPrediction methodMonte Carlo simulation of coherently scattered photons based on the inverse-sampling technique
Muhammad W, Liang Y, Hart GR, Nartowt BJ, Deng J. Monte Carlo simulation of coherently scattered photons based on the inverse-sampling technique. Acta Crystallographica Section A: Foundations And Advances 2020, 76: 70-78. PMID: 31908350, PMCID: PMC7045906, DOI: 10.1107/s2053273319014530.Peer-Reviewed Original ResearchComputational efficiencyAnomalous scattering factorsAtomic form factorsAcceptance-rejection techniqueScattering factorsMonte Carlo simulation packageMonte Carlo simulationsMonte Carlo packageAngular distributionsElastic scattering modelMonte Carlo modelTheoretical resultsSimulation algorithmMatrix calculationCarlo simulationsAnomalous scattering effectCarlo modelComplex systemsParticle transportForm factorsScattering modelSimulation accuracySimulation packageCoherent scatteringScattering effect
2019
Statistical Inference for Covariate-Adaptive Randomization Procedures
Ma W, Qin Y, Li Y, Hu F. Statistical Inference for Covariate-Adaptive Randomization Procedures. Journal Of The American Statistical Association 2019, 115: 1488-1497. DOI: 10.1080/01621459.2019.1635483.Peer-Reviewed Original ResearchCovariate-adaptive randomizationCovariate-adaptiveCovariate-adaptive randomization proceduresProperties of statistical methodsTheoretical resultsRandomization procedureLinear model frameworkAsymptotic representationCoin designTheoretical propertiesStatistical inferenceCovariate informationSimulation studySequential randomizationCovariate balanceInference propertiesSupplementary materialsComplete randomizationGeneral theoryBalanced treatment groupsCovariatesInferenceStatistical methodsRerandomizationRandomization
2014
A data-adaptive strategy for inverse weighted estimation of causal effects
Zhu Y, Ghosh D, Mitra N, Mukherjee B. A data-adaptive strategy for inverse weighted estimation of causal effects. Health Services And Outcomes Research Methodology 2014, 14: 69-91. DOI: 10.1007/s10742-014-0124-y.Peer-Reviewed Original ResearchEstimation of causal effectsData analysis examplesAverage treatment effectNonparametric modelSimulation studyTheoretical resultsPropensity scoreEffect of confoundersMeasured covariatesWeight estimationCausal effectsNonrandomized observational studyTreatment effectsLogistic regressionObservational studyAnalysis exampleRandomized trialsConfoundingExamplesScoresCovariatesInferenceEstimation
2012
Sparse principal component analysis by choice of norm
Qi X, Luo R, Zhao H. Sparse principal component analysis by choice of norm. Journal Of Multivariate Analysis 2012, 114: 127-160. PMID: 23524453, PMCID: PMC3601508, DOI: 10.1016/j.jmva.2012.07.004.Peer-Reviewed Original ResearchHigh-dimensional situationsSparse principal component analysisReal gene expression dataEfficient iterative algorithmHigh-dimensional dataSparse principal component analysis methodEigenvalue problemOptimization problemIterative methodChoice of normDimensional situationTheoretical resultsTraditional eigenvalue problemIterative algorithmStrict convexityLinear combinationSingle-component modelExpensive computationSparse linear combinationDimensional dataUsual normExistence of correlationsGene expression dataPractical applicationsCompetitive results
2007
Statistical Analysis of Diffusion Tensors in Diffusion-Weighted Magnetic Resonance Imaging Data
Zhu H, Zhang H, Ibrahim J, Peterson B. Statistical Analysis of Diffusion Tensors in Diffusion-Weighted Magnetic Resonance Imaging Data. Journal Of The American Statistical Association 2007, 102: 1085-1102. DOI: 10.1198/016214507000000581.Peer-Reviewed Original Research
2006
Generalized score test of homogeneity for mixed effects models
Zhu H, Zhang H. Generalized score test of homogeneity for mixed effects models. The Annals Of Statistics 2006, 34: 1545-1569. DOI: 10.1214/009053606000000380.Peer-Reviewed Original ResearchTest statisticsAsymptotic distributionRandom quadratic formsGeneralized score testQuadratic formInvariance principleScore testTest of homogeneityLatent variable modelsSimulation studyResampling procedureRestrictive assumptionsEmpirical performanceHomogeneity hypothesisTheoretical resultsVariance componentsVariable modelTest procedureBiomedical studiesMild conditionsInvarianceOverdispersionImportant problemsAssumptionsObservational data
2003
Hypothesis testing in mixture regression models
Zhu H, Zhang H. Hypothesis testing in mixture regression models. Journal Of The Royal Statistical Society Series B Statistical Methodology 2003, 66: 3-16. DOI: 10.1046/j.1369-7412.2003.05379.x.Peer-Reviewed Original ResearchMixture regression modelLikelihood estimatorTest statisticLog-likelihood ratio test statisticOptimal convergence ratesMaximum likelihoodRatio test statisticAsymptotic theoryReal data setsAsymptotic distributionConvergence rateTheoretical resultsEmpirical performanceReasonable conditionsSimulation studyHypothesis testingEstimatorStatisticsData setsRegression modelsModelTheoryDistribution
1999
On a Randomization Procedure in Linkage Analysis
Zhao H, Merikangas K, Kidd K. On a Randomization Procedure in Linkage Analysis. American Journal Of Human Genetics 1999, 65: 1449-1456. PMID: 10521312, PMCID: PMC1288298, DOI: 10.1086/302607.Peer-Reviewed Original ResearchConceptsEfficient simulation procedureObserved test statisticSimulation-based methodTheoretical resultsTest statisticNovel simulation methodSimulation methodReal dataSimulation procedureUninformative markersTheoretical workStatistical testsPedigree structureGenomewide significance levelRandomization procedureDiabetes dataStatisticsA more powerful method to evaluate p‐values in GENEHUNTER
Zhao H, Sheffield L, Pakstis A, Knauert M, Kidd K. A more powerful method to evaluate p‐values in GENEHUNTER. Genetic Epidemiology 1999, 17: s415-s420. PMID: 10597472, DOI: 10.1002/gepi.1370170770.Peer-Reviewed Original Research
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