Publication | Open Access
Making inferences on treatment effects from real world data: propensity scores, confounding by indication, and other perils for the unwary in observational research
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Citations
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References
2013
Year
Evidence-based InterventionField ExperimentTreatment EffectQuasi-experimentCausal InferenceBiasClinical TrialsRandomized Controlled TrialObservational ResearchPublic HealthStatisticsReal World DataOutcomes ResearchMarginal Structural ModelsEpidemiologyTreatment EffectsPropensity ScoreClinical EffectivenessTime-varying ConfoundingMedicineReal World Evidence
Propensity score based methods are used increasingly to evaluate the effectiveness of treatments when evidence from randomised trials is not available. However, users need to be aware of their strengths and limitations
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