2023
A mixed model approach to estimate the survivor average causal effect in cluster‐randomized trials
Wang W, Tong G, Hirani S, Newman S, Halpern S, Small D, Li F, Harhay M. A mixed model approach to estimate the survivor average causal effect in cluster‐randomized trials. Statistics In Medicine 2023, 43: 16-33. PMID: 37985966, DOI: 10.1002/sim.9939.Peer-Reviewed Original ResearchAgedHumansModels, StatisticalOutcome Assessment, Health CareQuality of LifeRandomized Controlled Trials as TopicSurvivorsSample size considerations for assessing treatment effect heterogeneity in randomized trials with heterogeneous intracluster correlations and variances
Tong G, Taljaard M, Li F. Sample size considerations for assessing treatment effect heterogeneity in randomized trials with heterogeneous intracluster correlations and variances. Statistics In Medicine 2023, 42: 3392-3412. PMID: 37316956, DOI: 10.1002/sim.9811.Peer-Reviewed Original ResearchConceptsGroup treatment trialsTreatment effect modificationRandomized trialsTreatment trialsEffect modificationEffect modifiersIntracluster correlation coefficientIndividual-level effect modifiersStudy armsTreatment effect heterogeneityOutcome observationsContinuous outcomesTrialsGroup treatmentTreatment effectsOutcome varianceEffect heterogeneityIntracluster correlationSample sizeSample size formulaAccounting for expected attrition in the planning of cluster randomized trials for assessing treatment effect heterogeneity
Tong J, Li F, Harhay M, Tong G. Accounting for expected attrition in the planning of cluster randomized trials for assessing treatment effect heterogeneity. BMC Medical Research Methodology 2023, 23: 85. PMID: 37024809, PMCID: PMC10077680, DOI: 10.1186/s12874-023-01887-8.Peer-Reviewed Original ResearchMeSH KeywordsCluster AnalysisComputer SimulationData Interpretation, StatisticalHumansModels, StatisticalRandomized Controlled Trials as TopicResearch DesignSample SizeConceptsSample size methodsSample size proceduresSize proceduresTreatment effect heterogeneityHeterogeneous treatment effectsSize methodMissingness ratesSample size formulaSample size estimationMissingness indicatorsEffect heterogeneityReal-world examplesSimulation studyIntracluster correlation coefficientInflation methodSize formulaAverage treatment effectResultsSimulation resultsSample size estimatesSize estimationMissingnessSample sizeClustersEstimationFormulaA scoping review described diversity in methods of randomization and reporting of baseline balance in stepped-wedge cluster randomized trials
Nevins P, Davis-Plourde K, Pereira Macedo J, Ouyang Y, Ryan M, Tong G, Wang X, Meng C, Ortiz-Reyes L, Li F, Caille A, Taljaard M. A scoping review described diversity in methods of randomization and reporting of baseline balance in stepped-wedge cluster randomized trials. Journal Of Clinical Epidemiology 2023, 157: 134-145. PMID: 36931478, PMCID: PMC10546924, DOI: 10.1016/j.jclinepi.2023.03.010.Peer-Reviewed Original ResearchMeSH KeywordsCluster AnalysisCross-Sectional StudiesHumansRandom AllocationRandomized Controlled Trials as TopicResearch DesignConceptsStepped-wedge clusterIndividual-level characteristicsMethod of randomizationCross-sectional designControl armBaseline imbalancesCohort designMedian numberElectronic searchPrimary analysisBaseline balanceStudy designPrimary reportsBaselineTrialsIntervention conditionSW-CRTsRandomizationReportingA Bayesian Approach for Estimating the Survivor Average Causal Effect When Outcomes Are Truncated by Death in Cluster-Randomized Trials
Tong G, Li F, Chen X, Hirani S, Newman S, Wang W, Harhay M. A Bayesian Approach for Estimating the Survivor Average Causal Effect When Outcomes Are Truncated by Death in Cluster-Randomized Trials. American Journal Of Epidemiology 2023, 192: 1006-1015. PMID: 36799630, PMCID: PMC10236525, DOI: 10.1093/aje/kwad038.Peer-Reviewed Original ResearchAgedBayes TheoremHumansModels, StatisticalQuality of LifeRandomized Controlled Trials as TopicSurvivors
2021
Accounting for unequal cluster sizes in designing cluster randomized trials to detect treatment effect heterogeneity
Tong G, Esserman D, Li F. Accounting for unequal cluster sizes in designing cluster randomized trials to detect treatment effect heterogeneity. Statistics In Medicine 2021, 41: 1376-1396. PMID: 34923655, PMCID: PMC10197222, DOI: 10.1002/sim.9283.Peer-Reviewed Original ResearchAgedCluster AnalysisHumansLinear ModelsRandomized Controlled Trials as TopicResearch DesignSample SizeSample size estimation for modified Poisson analysis of cluster randomized trials with a binary outcome
Li F, Tong G. Sample size estimation for modified Poisson analysis of cluster randomized trials with a binary outcome. Statistical Methods In Medical Research 2021, 30: 1288-1305. PMID: 33826454, PMCID: PMC9132618, DOI: 10.1177/0962280221990415.Peer-Reviewed Original ResearchMeSH KeywordsCluster AnalysisComputer SimulationModels, StatisticalRandomized Controlled Trials as TopicRiskSample SizeConceptsSample size formulaExchangeable working correlationExtensive Monte Carlo simulation studySize formulaMonte Carlo simulation studyFinite sample correctionMarginal relative riskCorresponding sample size formulaeSandwich variance estimatorVariable cluster sizesNumber of clustersAsymptotic efficiencySandwich varianceCluster size variabilityRobust sandwich varianceSample size estimationVariance estimatorAnalytical derivationSimulation studyCluster sizePoisson modelCoefficient estimatesFormulaCorrelation coefficient estimatesBinary outcomesSample size and power considerations for cluster randomized trials with count outcomes subject to right truncation
Li F, Tong G. Sample size and power considerations for cluster randomized trials with count outcomes subject to right truncation. Biometrical Journal 2021, 63: 1052-1071. PMID: 33751620, PMCID: PMC9132617, DOI: 10.1002/bimj.202000230.Peer-Reviewed Original ResearchConceptsCluster Randomized TrialPrimary outcomeGroup-based interventionRandomized trialsHealth StudySuch trialsPublic health studiesRight truncationTrialsOutcomesVector-borne diseasesCountSample size formulaAnalysis of CRTsPower calculationPopulation-level effectsSample sizeSize formulaClosed-form sample size formulaMarginal modeling approachMalariaDisease