Multiply robust estimation of principal causal effects with noncompliance and survival outcomes
Cheng C, Guo Y, Liu B, Wruck L, Li F, Li F. Multiply robust estimation of principal causal effects with noncompliance and survival outcomes. Clinical Trials 2024, 21: 553-561. PMID: 38813813, DOI: 10.1177/17407745241251773.Peer-Reviewed Original ResearchConceptsPrincipal strataRight-censored survival outcomesPrincipal causal effectsCausal effectsSensitivity analysis strategyPrincipal ignorabilityRobust estimationIdentification assumptionsCensoringPragmatic clinical trialsTreatment assignmentTreatment noncomplianceMonotonicityEstimationAssess treatment effectsCardiovascular diseaseClinical trialsMultipliersTreatment effectsAssumptionsNoncomplianceDoubly robust estimation and sensitivity analysis for marginal structural quantile models
Cheng C, Hu L, Li F. Doubly robust estimation and sensitivity analysis for marginal structural quantile models. Biometrics 2024, 80: ujae045. PMID: 38884127, DOI: 10.1093/biomtc/ujae045.Peer-Reviewed Original ResearchConceptsQuantile modelDistribution of potential outcomesEfficient influence functionPotential outcome distributionsDoubly robust estimatorsTime-varying treatmentsSequential ignorability assumptionSemiparametric frameworkIgnorability assumptionVariance estimationOutcome distributionInfluence functionRobust estimationPotential outcomesEfficient computationFunction approachTime-varying confoundersElectronic health record dataEstimationTreatment assignmentHealth record dataEffect of antihypertensive medicationEquationsRecord dataAntihypertensive medicationsMultiply 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 ProjectTransporting randomized trial results to estimate counterfactual survival functions in target populations
Cao Z, Cho Y, Li F. Transporting randomized trial results to estimate counterfactual survival functions in target populations. Pharmaceutical Statistics 2024, 23: 442-465. PMID: 38233102, DOI: 10.1002/pst.2354.Peer-Reviewed Original ResearchSurvival functionFinite-sample performanceSample average treatment effectApproximate variance estimatorsIncorrect model specificationAverage treatment effectRight censoringDistributions of treatment effect modifiersVariance estimationInverse probability weightingSimulation studyRobust estimationComplex surveysAverage treatmentProbability weightingTreatment effect modifiersEstimationTreatment effectsModel specificationCensoringTarget populationDifferential distributionSurvey weightsEffect modifiersFunction
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