2023
Accounting 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 ResearchConceptsSample 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 sizeClustersEstimationFormula
2022
Two weights make a wrong: Cluster randomized trials with variable cluster sizes and heterogeneous treatment effects
Wang X, Turner EL, Li F, Wang R, Moyer J, Cook AJ, Murray DM, Heagerty PJ. Two weights make a wrong: Cluster randomized trials with variable cluster sizes and heterogeneous treatment effects. Contemporary Clinical Trials 2022, 114: 106702. PMID: 35123029, PMCID: PMC8936048, DOI: 10.1016/j.cct.2022.106702.Peer-Reviewed Original ResearchConceptsInverse cluster sizeVariable cluster sizesCluster sizeCorrelation matrixTreatment effect estimatesCluster correlationEquation frameworkEstimation characteristicsTheoretical derivationSimulation studyAverage treatment effectHeterogeneous treatment effectsDistinct weightsEstimandsCluster levelHierarchical nestingMatrixHypothetical populationEstimatesValid resultsDerivationClustersConceptual populationEstimationEffect estimates
2021
Power considerations for generalized estimating equations analyses of four‐level cluster randomized trials
Wang X, Turner EL, Preisser JS, Li F. Power considerations for generalized estimating equations analyses of four‐level cluster randomized trials. Biometrical Journal 2021, 64: 663-680. PMID: 34897793, PMCID: PMC9574475, DOI: 10.1002/bimj.202100081.Peer-Reviewed Original ResearchConceptsCorrelation structureClosed-form sample size formulaModel-based varianceTrue correlation structureSandwich variance estimatorSandwich varianceSample size formulaVariance functionVariance estimatorEmpirical powerCorrelation parametersCorrelation matrixEstimating EquationsSize formulaEquationsArbitrary linkPower considerationsSame clusterPower calculationEstimatorSample sizeEquation analysisClustersFormula
2020
Mixed-effects models for the design and analysis of stepped wedge cluster randomized trials: An overview
Li F, Hughes JP, Hemming K, Taljaard M, Melnick ER, Heagerty PJ. Mixed-effects models for the design and analysis of stepped wedge cluster randomized trials: An overview. Statistical Methods In Medical Research 2020, 30: 612-639. PMID: 32631142, PMCID: PMC7785651, DOI: 10.1177/0962280220932962.Peer-Reviewed Original Research
2019
Design and analysis considerations for cohort stepped wedge cluster randomized trials with a decay correlation structure
Li F. Design and analysis considerations for cohort stepped wedge cluster randomized trials with a decay correlation structure. Statistics In Medicine 2019, 39: 438-455. PMID: 31797438, PMCID: PMC7027591, DOI: 10.1002/sim.8415.Peer-Reviewed Original ResearchConceptsQuasi-least squaresCorrelation structureAdditional correlation parameterCluster correlation structureCorrelation parametersSample size proceduresPeriod correlationMultiple outcome measurementsSandwich varianceCorrelation decayPower proceduresSize proceduresEmpirical powerSimulation studySame clusterTrial exampleSquaresAnalysis considerationsWedge designParametersSample sizeContinuous outcomesClusters