2024
Optimal designs using generalized estimating equations in cluster randomized crossover and stepped wedge trials
Liu J, Li F. Optimal designs using generalized estimating equations in cluster randomized crossover and stepped wedge trials. Statistical Methods In Medical Research 2024, 33: 1299-1330. PMID: 38813761, DOI: 10.1177/09622802241247717.Peer-Reviewed Original ResearchConceptsMaximin optimal designsStepped wedge cluster randomized trialLocally optimal designsCluster-period sizesClosed-form formulaCluster-randomized crossover trialCross-sectional sampling schemeInteger estimationOptimal design algorithmDesign algorithmLongitudinal cluster randomized trialsWorking correlation structureCluster randomized trialMethod of generalized estimating equationsTreatment effect estimatesSAS macroVariance expressionsExact valueCorrelation structureMaximinSampling schemeBetween-clusterOptimal designOptimization design researchEstimating equationsDemystifying estimands in cluster-randomised trials
Kahan B, Blette B, Harhay M, Halpern S, Jairath V, Copas A, Li F. Demystifying estimands in cluster-randomised trials. Statistical Methods In Medical Research 2024, 33: 1211-1232. PMID: 38780480, PMCID: PMC11348634, DOI: 10.1177/09622802241254197.Peer-Reviewed Original ResearchCluster randomised trialPotential outcomes notationTreatment effect estimatesOverview of estimationPublished cluster randomised trialsCluster-level summariesTarget estimandEstimandsTreatment effectsEffect estimatesInterpretation of treatment effectsOdds ratioEstimationRandomised trialsStudy objective
2023
Informative cluster size in cluster-randomised trials: A case study from the TRIGGER trial
Kahan B, Li F, Blette B, Jairath V, Copas A, Harhay M. Informative cluster size in cluster-randomised trials: A case study from the TRIGGER trial. Clinical Trials 2023, 20: 661-669. PMID: 37439089, PMCID: PMC10638852, DOI: 10.1177/17407745231186094.Peer-Reviewed Original ResearchConceptsCluster-randomised trialCluster-level summariesAcute upper gastrointestinal bleedingExchangeable correlation structureRed blood cell transfusionEQ-5D VAS scoreMixed-effects modelsUpper gastrointestinal bleedingBlood cell transfusionMixed effects modelsTreatment effectsCell transfusionGastrointestinal bleedingIschemic eventsVAS scoresOdds ratioMost outcomesTRIGGER trialTreatment effect estimatesEffect estimatesInformative cluster sizeTrialsOutcomesParticipant outcomesCorrelation structure
2022
Assessing Exposure-Time Treatment Effect Heterogeneity in Stepped-Wedge Cluster Randomized Trials
Maleyeff L, Li F, Haneuse S, Wang R. Assessing Exposure-Time Treatment Effect Heterogeneity in Stepped-Wedge Cluster Randomized Trials. Biometrics 2022, 79: 2551-2564. PMID: 36416302, PMCID: PMC10203056, DOI: 10.1111/biom.13803.Peer-Reviewed Original ResearchConceptsTreatment effect heterogeneityEffect heterogeneityParameter increasesTreatment effect parametersParametric functional formModel choicePermutation testModel formulationSimulation studyPrecise averageNew model formulationFunctional formEffect parametersRandom effectsTreatment effect estimatesCategorical termsVariance componentsTwo 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
2018
Addressing Extreme Propensity Scores via the Overlap Weights
Li F, Thomas L, Li F. Addressing Extreme Propensity Scores via the Overlap Weights. American Journal Of Epidemiology 2018, 188: 250-257. PMID: 30189042, DOI: 10.1093/aje/kwy201.Peer-Reviewed Original ResearchConceptsPropensity score distributionInverse probability weighting methodConfidence interval coverageOverlap weightingProbability weighting methodTreatment effect estimatesPropensity scoreInterval coverageScore distributionEffect estimatesTarget populationOverlap weighting methodExcess varianceInverse probabilityCutoff pointStandard error
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