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Using Inverse Probability-Weighted Estimators in Comparative Effectiveness Analyses With Observational Databases
501
Citations
22
References
2007
Year
EngineeringTreatment EffectQuasi-experimentObservational DatabasesInverse Probability-weighted EstimatorsCausal InferencePreventive MedicineBiasManagementRandomized Controlled TrialPublic HealthStatisticsMedical StatisticComparative EffectivenessSelection BiasHealth PolicyComparative Effectiveness AnalysesEstimation StatisticInverse Probability-weighted EstimationEpidemiologyMore TreatmentsStatistical InferenceSurvey Methodology
Inverse probability-weighted estimation is a powerful tool for use with observational data. In this article, we describe how this propensity score-based method can be used to compare the effectiveness of 2 or more treatments. First, we discuss the inherent problems in using observational data to assess comparative effectiveness. Next, we provide a conceptual explanation of inverse probability-weighted estimation and point readers to sources that address the method in more formal, technical terms. Finally, we offer detailed guidance about how to implement the estimators in comparative effectiveness analyses.
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