2024
Use of random integration to test equality of high dimensional covariance matrices.
Jiang Y, Wen C, Jiang Y, Wang X, Zhang H. Use of random integration to test equality of high dimensional covariance matrices. Statistica Sinica 2024, 33: 2359-2380. PMID: 37799490, PMCID: PMC10550010, DOI: 10.5705/ss.202020.0486.Peer-Reviewed Original Research
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
2016
Testing Violations of the Exponential Assumption in Cancer Clinical Trials with Survival Endpoints
Han G, Schell MJ, Zhang H, Zelterman D, Pusztai L, Adelson K, Hatzis C. Testing Violations of the Exponential Assumption in Cancer Clinical Trials with Survival Endpoints. Biometrics 2016, 73: 687-695. PMID: 27669414, PMCID: PMC6093291, DOI: 10.1111/biom.12590.Peer-Reviewed Original Research