2024
A review of current practice in the design and analysis of extremely small stepped-wedge cluster randomized trials.
Tong G, Nevins P, Ryan M, Davis-Plourde K, Ouyang Y, Pereira Macedo J, Meng C, Wang X, Caille A, Li F, Taljaard M. A review of current practice in the design and analysis of extremely small stepped-wedge cluster randomized trials. Clinical Trials 2024, 17407745241276137. PMID: 39377196, DOI: 10.1177/17407745241276137.Peer-Reviewed Original ResearchSmall-sample correctionsStepped-wedge cluster randomized trialCluster randomized trialSample size calculation methodGeneralized linear mixed modelsLongitudinal correlation structureSize calculation methodLinear mixed modelsPermutation testSample sizeBayesian approachRandomized trialsCorrelation structureMixed modelsBayesian analysisGeneralized estimating equationsPermutationMedian sample sizeIntervention conditionRandomization methodEquationsAssessing treatment effect heterogeneity in the presence of missing effect modifier data in cluster-randomized trials
Blette B, Halpern S, Li F, Harhay M. Assessing treatment effect heterogeneity in the presence of missing effect modifier data in cluster-randomized trials. Statistical Methods In Medical Research 2024, 33: 909-927. PMID: 38567439, PMCID: PMC11041086, DOI: 10.1177/09622802241242323.Peer-Reviewed Original ResearchConceptsMultilevel multiple imputationHeterogeneous treatment effectsCluster randomized trialPotential effect modifiersMultiple imputationAssess treatment effect heterogeneityEffect modifiersTreatment effect heterogeneityComplete-case analysisMissingness mechanismIntracluster correlationSimulation studyUnder-coverageRandomized trialsEffect heterogeneityHealth StudyTreatment effectsContinuous outcomesClinical practiceImputationModel specificationMissingnessData methodsModified dataTrialsMultiply robust generalized estimating equations for cluster randomized trials with missing outcomes
Rabideau D, Li F, Wang R. Multiply robust generalized estimating equations for cluster randomized trials with missing outcomes. Statistics In Medicine 2024, 43: 1458-1474. PMID: 38488532, DOI: 10.1002/sim.10027.Peer-Reviewed Original ResearchPropensity score modelMarginal regression parametersWeighted generalized estimating equationsRobust estimationCluster randomized trialRegression parametersMarginal meansMean modelIterative algorithmMonte Carlo simulationsGeneralized estimating equationsOutcome modelBotswana Combination Prevention ProjectCarlo simulationsEquationsCorrelation parametersEstimationReduce HIV incidenceHIV prevention measuresScore modelMultipliersRandomized trialsHIV incidencePrevention ProjectCRTFASTGEEPWR: A SAS Macro for Power of Generalized Estimating Equations Analysis of Multi-Period Cluster Randomized Trials with Application to Stepped Wedge Designs
Zhang Y, Preisser J, Li F, Turner E, Rathouz P. CRTFASTGEEPWR: A SAS Macro for Power of Generalized Estimating Equations Analysis of Multi-Period Cluster Randomized Trials with Application to Stepped Wedge Designs. Journal Of Statistical Software 2024, 108: 1-27. DOI: 10.18637/jss.v108.c01.Peer-Reviewed Original ResearchSAS macroMarginal mean modelCluster randomized trialContinuous responseStepped wedge designMean modelCorrelation structureGeneralized estimating equationsPower methodIncomplete designsGeneral methodWedge designStatistical powerTrial scenariosMulti-parameterEvaluation of interventionsRandomized trialsGeneralized estimating equation analysisEquationsInference
2023
Sample 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 formula
2022
Stepped Wedge Cluster Randomized Trials: A Methodological Overview
Li F, Wang R. Stepped Wedge Cluster Randomized Trials: A Methodological Overview. World Neurosurgery 2022, 161: 323-330. PMID: 35505551, PMCID: PMC9074087, DOI: 10.1016/j.wneu.2021.10.136.Peer-Reviewed Original ResearchConceptsStepped wedge designStepped wedge cluster randomized trialIntervention programsSample size determinationDelivery of patient careWedge designStepped wedge trial designHealth intervention programsCluster randomized trialRandomized trialsPatient careStudy designPragmatic settingSize determinationTrial designGeneralizing Trial Evidence to Target Populations in Non-Nested Designs: Applications to AIDS Clinical Trials
Li F, Buchanan AL, Cole SR. Generalizing Trial Evidence to Target Populations in Non-Nested Designs: Applications to AIDS Clinical Trials. Journal Of The Royal Statistical Society Series C (Applied Statistics) 2022, 71: 669-697. PMID: 35968541, PMCID: PMC9367209, DOI: 10.1111/rssc.12550.Peer-Reviewed Original ResearchAIDS Clinical Trials GroupTarget populationClinical Trials GroupComparative effectiveness evidenceTreatment effectsRandomized trialsTrial evidenceClinical trialsTrial groupHIV interventionsACTG trialsTrial participantsTrial designPropensity scoreEffectiveness evidenceTrialsAIDS clinical trialsSpecified populationPopulationAverage treatment effectMost casesHIVEvidenceRegression
2021
A note on semiparametric efficient generalization of causal effects from randomized trials to target populations
Li F, Hong H, Stuart E. A note on semiparametric efficient generalization of causal effects from randomized trials to target populations. Communication In Statistics- Theory And Methods 2021, 52: 5767-5798. PMID: 37484707, PMCID: PMC10361688, DOI: 10.1080/03610926.2021.2020291.Peer-Reviewed Original ResearchMethodological challenges in pragmatic trials in Alzheimer’s disease and related dementias: Opportunities for improvement
Taljaard M, Li F, Qin B, Cui C, Zhang L, Nicholls SG, Carroll K, Mitchell SL. Methodological challenges in pragmatic trials in Alzheimer’s disease and related dementias: Opportunities for improvement. Clinical Trials 2021, 19: 86-96. PMID: 34841910, PMCID: PMC8847324, DOI: 10.1177/17407745211046672.Peer-Reviewed Original ResearchConceptsPragmatic trialAlzheimer's diseasePrimary outcomeSample size calculationGroup treatment trialsPairs of reviewersDementia researchSize calculationCluster Randomized TrialGroup treatment designRandomized trialsTreatment trialsIntracluster correlationMethodological qualityTrial reportsBaseline assessmentDiseaseTrialsDementiaKey methodological characteristicsOutcomesType IMethodological quality indicatorsUnique methodological challengesSame individualSample 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
2019
cvcrand: A Package for Covariate-constrained Randomization and the Clustered Permutation Test for Cluster Randomized Trials
Yu H, Li F, Gallis J, Turner E. cvcrand: A Package for Covariate-constrained Randomization and the Clustered Permutation Test for Cluster Randomized Trials. The R Journal 2019, 11: 191. DOI: 10.32614/rj-2019-027.Peer-Reviewed Original Research