2025
Outcome adaptive propensity score methods for handling censoring and high-dimensionality: Application to insurance claims
Du J, Yu Y, Zhang M, Wu Z, Ryan A, Mukherjee B. Outcome adaptive propensity score methods for handling censoring and high-dimensionality: Application to insurance claims. Statistical Methods In Medical Research 2025, 34: 847-866. PMID: 40013476, DOI: 10.1177/09622802241306856.Peer-Reviewed Original ResearchPropensity score modelHigh-dimensional settingsVariable selection procedureTreatment effect estimatesPropensity score estimationAverage treatment effectVariable selection methodsModel misspecificationMultiple treatment groupsSimulation studyRegularization methodStatistical efficiencyBinary outcomesScore estimationOutcome probabilitiesSelection procedureHigh-dimensionalTreatment effectsEffect estimatesVariables related to treatmentCensoringPropensity scoreMisspecificationEstimationPropensity score methodsNote on targeted learning with an undersmoothed Lasso propensity score model for large-scale covariate adjustment in health care database studies
Wyss R, van der Laan M, Gruber S, Shi X, Lee H, Dutcher S, Nelson J, Toh S, Russo M, Wang S, Desai R, Lin K. Note on targeted learning with an undersmoothed Lasso propensity score model for large-scale covariate adjustment in health care database studies. American Journal Of Epidemiology 2025, 194: 1470-1472. PMID: 40036894, DOI: 10.1093/aje/kwaf024.Peer-Reviewed Original ResearchCovariate adjustmentPropensity score model
2024
Targeted learning with an undersmoothed LASSO propensity score model for large-scale covariate adjustment in health-care database studies
Wyss R, van der Laan M, Gruber S, Shi X, Lee H, Dutcher S, Nelson J, Toh S, Russo M, Wang S, Desai R, Lin K. Targeted learning with an undersmoothed LASSO propensity score model for large-scale covariate adjustment in health-care database studies. American Journal Of Epidemiology 2024, 193: 1632-1640. PMID: 38517025, PMCID: PMC11538566, DOI: 10.1093/aje/kwae023.Peer-Reviewed Original ResearchConfounding controlLarge-scale propensity scoreDatabase studyPropensity scoreHealthcare database studiesCovariate distributionsPS modelCovariate adjustmentReduce biasData-adaptivePropensity score modelNon-overlappingEstimate treatment effectsCovariate overlapCross-fittingHealthcareTarget learningConfoundingRobust frameworkUndersmoothingCollaborative learningTreatment effectsLearningLASSOLASSO regressionReal-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial*
Levin M, Kia A, Timsina P, Cheng F, Nguyen K, Kohli-Seth R, Lin H, Ouyang Y, Freeman R, Reich D. Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial*. Critical Care Medicine 2024, 52: 1007-1020. PMID: 38380992, DOI: 10.1097/ccm.0000000000006243.Peer-Reviewed Original ResearchConceptsIntervention groupPatient bed-daysBed daysRelative riskAdjusted incidence rate ratiosMedical-surgical unitsAssignment to interventionFront-line providersAdjusted relative risksIncidence rate ratiosIn-HospitalMedication ordersAdjusted RRClinical careRate ratiosStabilized inverse probabilityControl armPropensity score modelSecondary outcomesPrimary outcomePredicting clinical deteriorationActivation criteriaProspective dataLikelihood of deteriorationProvider discretionMultiply 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, PMCID: PMC12186826, 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 Project
2021
Impact of Obeticholic acid Exposure on Decompensation and Mortality in Primary Biliary Cholangitis and Cirrhosis
John BV, Schwartz K, Levy C, Dahman B, Deng Y, Martin P, Taddei TH, Kaplan DE. Impact of Obeticholic acid Exposure on Decompensation and Mortality in Primary Biliary Cholangitis and Cirrhosis. Hepatology Communications 2021, 5: 1426-1436. PMID: 34430786, PMCID: PMC8369937, DOI: 10.1002/hep4.1720.Peer-Reviewed Original ResearchPrimary biliary cholangitisLiver-related mortalityHepatic decompensationOCA useOCA usersPBC cirrhosisObeticholic acidPropensity score modelBiliary cholangitisScore modelRetrospective cohort studySerious liver injuryTreatment of patientsEffect of treatmentCohort studyPartial respondersLiver injuryMultivariable analysisPotential confoundersC-statisticUS veteransUrsodeoxycholic acidBaseline riskCirrhosisDecompensationCovariate adjustment in subgroup analyses of randomized clinical trials: A propensity score approach
Yang S, Li F, Thomas L, Li F. Covariate adjustment in subgroup analyses of randomized clinical trials: A propensity score approach. Clinical Trials 2021, 18: 570-581. PMID: 34269087, DOI: 10.1177/17407745211028588.Peer-Reviewed Original ResearchConceptsPropensity score weighting estimatorChance imbalanceAnalysis of randomized clinical trialsAnalysis of covariance estimatorSubgroup analyses of randomized clinical trialsCovariate adjustmentWeight estimationControlled Trial Investigating Outcomes of Exercise Training trialPropensity score weighting methodologyHeterogeneous treatment effectsRandomized clinical trialsCovariance estimationPropensity score modelPropensity modelAnalysis of covariancePropensity score weightingSubgroup sample sizeSubgroup analysisEffects of exercise trainingExercise training trialsOutcome modelScore weightingEvidence of heterogeneous treatment effectsCovariatesUnadjusted estimates
2016
Impact of point-of-care ultrasonography on ED time to disposition for patients with nontraumatic shock
Hall MK, Taylor RA, Luty S, Allen IE, Moore CL. Impact of point-of-care ultrasonography on ED time to disposition for patients with nontraumatic shock. The American Journal Of Emergency Medicine 2016, 34: 1022-1030. PMID: 26988105, DOI: 10.1016/j.ajem.2016.02.059.Peer-Reviewed Original ResearchConceptsPOC ultrasonographyEmergency departmentNontraumatic shockCare ultrasonographyPropensity scorePropensity score matchElectronic health recordsHospital mortalityShock patientsPrompt diagnosisED arrivalED patientsED physiciansPoint of careRetrospective studyUnique patientsImpact of pointMean reductionPropensity score modelPatientsUltrasonographyED timeDiagnostic ultrasonographyCovariates of timeEvidence of reduction
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply