2025
Power and Sample Size Calculations for Cluster Randomized Hybrid Type 2 Effectiveness‐Implementation Studies
Owen M, Curran G, Smith J, Tedla Y, Cheng C, Spiegelman D. Power and Sample Size Calculations for Cluster Randomized Hybrid Type 2 Effectiveness‐Implementation Studies. Statistics In Medicine 2025, 44: e70015. PMID: 39930740, DOI: 10.1002/sim.70015.Peer-Reviewed Original ResearchMeSH KeywordsCardiovascular DiseasesCluster AnalysisHumansModels, StatisticalRandomized Controlled Trials as TopicResearch DesignSample SizeConceptsHybrid type 2 effectiveness-implementation studySample size calculationCluster randomized trialCluster randomized designSize calculationImplementation research outcomesReduce cardiovascular diseaseIssue of multiple testingEffective outcomesImplementation outcomesCommunity interventionsControl blood pressureBinary outcomesOutcomes approachLiterature searchMultiple testingCardiovascular diseaseInterventionRandomized trialsStandard statistical methodsBlood pressureOutcomesType 2 studies
2021
swdpwr: A SAS macro and an R package for power calculations in stepped wedge cluster randomized trials
Chen J, Zhou X, Li F, Spiegelman D. swdpwr: A SAS macro and an R package for power calculations in stepped wedge cluster randomized trials. Computer Methods And Programs In Biomedicine 2021, 213: 106522. PMID: 34818620, PMCID: PMC8665077, DOI: 10.1016/j.cmpb.2021.106522.Peer-Reviewed Original ResearchMeSH KeywordsCluster AnalysisCross-Sectional StudiesHumansRandomized Controlled Trials as TopicResearch DesignSample SizeConceptsWedge clusterIntracluster correlation coefficientContinuous outcomesCross-sectional cohortBinary outcomesExchangeable correlation structureWedge designPublic health intervention evaluationsHealth services researchClosed cohort designPower calculationCohort designClosed cohortStudy designIntracluster correlationIntervention evaluationNeeds of investigatorsOutcomesTrialsCohortServices researchInvestigatorsPrevious studiesSWD
2019
On the analysis of two‐phase designs in cluster‐correlated data settings
Rivera‐Rodriguez C, Spiegelman D, Haneuse S. On the analysis of two‐phase designs in cluster‐correlated data settings. Statistics In Medicine 2019, 38: 4611-4624. PMID: 31359448, PMCID: PMC6736737, DOI: 10.1002/sim.8321.Peer-Reviewed Original ResearchConceptsSmall-sample operating characteristicsInverse probability weighting estimatorData settingClosed-form expressionTwo-phase designStatistical efficiencyComprehensive simulation studyWeighting estimatorCovariance structureSandwich estimatorInvalid inferencesValid inferencesSimulation studyCovariate dataInverse probability weightingEstimatorNaïve methodSampling designNovel analysis approachInferenceRobust sandwich estimatorAnalysis methodAnalysis approachNational antiretroviral treatment programmeCategorical risk
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