2023
An inverse probability weighted regression method that accounts for right‐censoring for causal inference with multiple treatments and a binary outcome
Yu Y, Zhang M, Mukherjee B. An inverse probability weighted regression method that accounts for right‐censoring for causal inference with multiple treatments and a binary outcome. Statistics In Medicine 2023, 42: 3699-3715. PMID: 37392070, DOI: 10.1002/sim.9826.Peer-Reviewed Original ResearchConceptsRight censoringWeighted score functionCausal treatment effectsAverage treatment effectAsymptotic propertiesCensored componentPre-specified time windowEstimation consistencyRobustness propertiesSimulation studyBinary outcomesPresence of confoundersCensoringScoring functionInverse probabilityTreatment effectsEstimationSources of biasInferenceLetter CComparative effectiveness researchTreatment switchRegression methodLogistic regression modelsInsurance claims database
2021
A comparison of parametric propensity score‐based methods for causal inference with multiple treatments and a binary outcome
Yu Y, Zhang M, Shi X, Caram M, Little R, Mukherjee B. A comparison of parametric propensity score‐based methods for causal inference with multiple treatments and a binary outcome. Statistics In Medicine 2021, 40: 1653-1677. PMID: 33462862, DOI: 10.1002/sim.8862.Peer-Reviewed Original ResearchConceptsComparative effectiveness researchEstimation of causal effectsPropensity score-based methodsBinary outcomesInsurance networksCausal effectsPropensity score methodsPropensity-based methodsConfounding biasContinuous outcomesPharmacy claimsEffectiveness researchObservational studySimulation studyAdverse outcomesPropensity scoreEmergency room