2020
Relative Efficiency of Using Summary Versus Individual Data in Random-Effects Meta-Analysis
Chen D, Liu D, Min X, Zhang H. Relative Efficiency of Using Summary Versus Individual Data in Random-Effects Meta-Analysis. Biometrics 2020, 76: 1319-1329. PMID: 32056197, PMCID: PMC7955582, DOI: 10.1111/biom.13238.Peer-Reviewed Original ResearchConceptsMaximum likelihood estimationSummary statisticsAsymptotic senseStatistical methodologyLikelihood estimationGaussian distributionInference settingHeterogeneity parametersRelative efficiencyRandom effectsSample sizeStatisticsInferenceData setsModelEfficient conclusionsEstimationIndividual participant dataAssumptionParametersEfficiency
2019
Stats: P values akin to ‘beyond reasonable doubt’
Zhang H. Stats: P values akin to ‘beyond reasonable doubt’. Nature 2019, 569: 336-336. PMID: 31097822, DOI: 10.1038/d41586-019-01530-x.Peer-Reviewed Original ResearchData Interpretation, StatisticalAn accurate and powerful method for copy number variation detection
Xiao F, Luo X, Hao N, Niu YS, Xiao X, Cai G, Amos CI, Zhang H. An accurate and powerful method for copy number variation detection. Bioinformatics 2019, 35: 2891-2898. PMID: 30649252, PMCID: PMC6735918, DOI: 10.1093/bioinformatics/bty1041.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAllelesData Interpretation, StatisticalDNA Copy Number VariationsGenome-Wide Association StudyPolymorphism, Single NucleotideSensitivity and SpecificitySoftwareConceptsHigh computational efficiency
2012
Multiscale Adaptive Marginal Analysis of Longitudinal Neuroimaging Data with Time-Varying Covariates
Skup M, Zhu H, Zhang H. Multiscale Adaptive Marginal Analysis of Longitudinal Neuroimaging Data with Time-Varying Covariates. Biometrics 2012, 68: 1083-1092. PMID: 22551084, PMCID: PMC3767131, DOI: 10.1111/j.1541-0420.2012.01767.x.Peer-Reviewed Original Research
2011
Statistical Inference in Mixed Models and Analysis of Twin and Family Data
Wang X, Guo X, He M, Zhang H. Statistical Inference in Mixed Models and Analysis of Twin and Family Data. Biometrics 2011, 67: 987-995. PMID: 21306354, PMCID: PMC3129472, DOI: 10.1111/j.1541-0420.2010.01548.x.Peer-Reviewed Original ResearchMeSH KeywordsBiometryData Interpretation, StatisticalFamily HealthGenetic Diseases, InbornGenetic Predisposition to DiseaseHumansInheritance PatternsModels, StatisticalTwin Studies as TopicConceptsStandard regularity conditionsStatistical inferenceAsymptotic distributionRegularity conditionsSufficient conditionsCholesky decompositionLikelihood ratio testComputational softwareLinear modelAdvanced theoryFamily data analysisImportant exampleRatio testFamily dataKey ideaPrecise estimatesMixed-effects modelsTheoryMixed effects modelsData setsIdentifiabilityModelEstimatesMixed modelsGeneral linear modelPropensity score‐based nonparametric test revealing genetic variants underlying bipolar disorder
Jiang Y, Zhang H. Propensity score‐based nonparametric test revealing genetic variants underlying bipolar disorder. Genetic Epidemiology 2011, 35: 125-132. PMID: 21254220, PMCID: PMC3077545, DOI: 10.1002/gepi.20558.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsGenetic variantsWellcome Trust Case Control ConsortiumRPGRIP1L geneGenetic studiesAssociation analysisHaplotype blocksChromosome 16Nucleotide polymorphismsComplex diseasesGenesComplex disorderStrong signalUnreported regionsVariantsImportant roleStrong evidencePolymorphismBipolar disorderRegionRegression and data mining methods for analyses of multiple rare variants in the Genetic Analysis Workshop 17 mini‐exome data
Bailey‐Wilson J, Brennan JS, Bull SB, Culverhouse R, Kim Y, Jiang Y, Jung J, Li Q, Lamina C, Liu Y, Mägi R, Niu YS, Simpson CL, Wang L, Yilmaz YE, Zhang H, Zhang Z. Regression and data mining methods for analyses of multiple rare variants in the Genetic Analysis Workshop 17 mini‐exome data. Genetic Epidemiology 2011, 35: s92-s100. PMID: 22128066, PMCID: PMC3360949, DOI: 10.1002/gepi.20657.Peer-Reviewed Original ResearchConceptsData mining methodsUse of machineMachine learning methodsMining methodsLearning methodsNovel methodGenetic Analysis Workshop 17 mini-exome dataGenetic Analysis Workshop 17Extreme locus heterogeneityDNA sequence dataLocus-specific heritabilityMultiple rare variantsPopulation-specific analysesRare variantsIndividual rare variantsRare genetic variantsRare causal variantsSubset of predictorsLarge numberMultiple variantsComplex traitsMachineSequence dataCausal variantsCausal mutations
2009
Analysis of Twin Data Using SAS
Feng R, Zhou G, Zhang M, Zhang H. Analysis of Twin Data Using SAS. Biometrics 2009, 65: 584-589. PMID: 18647295, PMCID: PMC2700843, DOI: 10.1111/j.1541-0420.2008.01098.x.Peer-Reviewed Original Research
2007
A forest-based approach to identifying gene and gene–gene interactions
Chen X, Liu CT, Zhang M, Zhang H. A forest-based approach to identifying gene and gene–gene interactions. Proceedings Of The National Academy Of Sciences Of The United States Of America 2007, 104: 19199-19203. PMID: 18048322, PMCID: PMC2148267, DOI: 10.1073/pnas.0709868104.Peer-Reviewed Original Research
2006
Family‐based association tests for ordinal traits adjusting for covariates
Wang X, Ye Y, Zhang H. Family‐based association tests for ordinal traits adjusting for covariates. Genetic Epidemiology 2006, 30: 728-736. PMID: 17086513, DOI: 10.1002/gepi.20184.Peer-Reviewed Original Research
1999
Analysis of Infant Growth Curves Using Multivariate Adaptive Splines
Zhang H. Analysis of Infant Growth Curves Using Multivariate Adaptive Splines. Biometrics 1999, 55: 452-459. PMID: 11318199, DOI: 10.1111/j.0006-341x.1999.00452.x.Peer-Reviewed Original Research
1996
A TREE‐BASED METHOD OF ANALYSIS FOR PROSPECTIVE STUDIES
ZHANG H, HOLFORD T, BRACKEN M. A TREE‐BASED METHOD OF ANALYSIS FOR PROSPECTIVE STUDIES. Statistics In Medicine 1996, 15: 37-49. PMID: 8614744, DOI: 10.1002/(sici)1097-0258(19960115)15:1<37::aid-sim144>3.0.co;2-0.Peer-Reviewed Original Research
1995
Tree-based Risk Factor Analysis of Preterm Delivery and Small-for-Gestational-Age Birth
Zhang H, Bracken M. Tree-based Risk Factor Analysis of Preterm Delivery and Small-for-Gestational-Age Birth. American Journal Of Epidemiology 1995, 141: 70-78. PMID: 7801968, DOI: 10.1093/oxfordjournals.aje.a117347.Peer-Reviewed Original ResearchMeSH KeywordsBlack PeopleData Interpretation, StatisticalEpidemiologic MethodsFemaleHumansInfant, NewbornInfant, PrematureInfant, Small for Gestational AgeObstetric Labor, PrematurePregnancyRisk FactorsConceptsPreterm deliveryYale-New Haven HospitalGestational age infantsGestational-age birthsRisk factor analysisPutative risk factorsPassive smokingGestational ageAge infantsMaternal ageRisk factorsCaffeine consumptionSecondary analysisAlcohol useMarital statusSmokingBlack womenMarijuana useAgeOutcomesDeliveryNew Haven