2023
Competing risks regression for clustered survival data via the marginal additive subdistribution hazards model
Chen X, Esserman D, Li F. Competing risks regression for clustered survival data via the marginal additive subdistribution hazards model. Statistica Neerlandica 2023, 78: 281-301. DOI: 10.1111/stan.12317.Peer-Reviewed Original ResearchSandwich variance estimatorCorrelated failure time dataVariance estimatorUnknown dependency structureFailure time dataAdditive hazards modelFinite samplesEquation approachCensoring timeCorrelation structureAdditive structureDependent censoringFit testSimulation studyEvent of interestDependency structureFailure timeEstimatorSubdistribution hazardRegression coefficientsIncidence functionCumulative incidence functionSubdistribution hazard modelTime dataOverall model
2022
Design and analysis of cluster randomized trials with time‐to‐event outcomes under the additive hazards mixed model
Blaha O, Esserman D, Li F. Design and analysis of cluster randomized trials with time‐to‐event outcomes under the additive hazards mixed model. Statistics In Medicine 2022, 41: 4860-4885. PMID: 35908796, PMCID: PMC9588628, DOI: 10.1002/sim.9541.Peer-Reviewed Original ResearchConceptsSample size formulaCluster sizeNew sample size formulaSample size proceduresSize formulaEffect parametersSandwich variance estimatorStatistical inferenceCluster size variationEvent outcomesRandomization-based testsImproved inferenceSize proceduresTreatment effect parametersVariance estimatorSmall sample biasesAnalysis of clustersSimulation studyUnequal cluster sizesFrailty termVariance inflation factorFailure timeSample size requirementsMixed modelsAppropriate definition