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Inverse probability of treatment weighting

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Full-Text Articles in Biostatistics

Moving Towards Best Practice When Using Inverse Probability Of Treatment Weighting (Iptw) Using The Propensity Score To Estimate Causal Treatment Effects In Observational Studies, Peter Austin, Elizabeth Stuart Jan 2015

Moving Towards Best Practice When Using Inverse Probability Of Treatment Weighting (Iptw) Using The Propensity Score To Estimate Causal Treatment Effects In Observational Studies, Peter Austin, Elizabeth Stuart

Peter Austin

The propensity score is defined as a subject’s probability of treatment selection, conditional on observed baseline covariates.Weighting subjects by the inverse probability of treatment received creates a synthetic sample in which treatment assignment is independent of measured baseline covariates. Inverse probability of treatment weighting (IPTW) using the propensity score allows one to obtain unbiased estimates of average treatment effects. However, these estimates are only valid if there are no residual systematic differences in observed baseline characteristics between treated and control subjects in the sample weighted by the estimated inverse probability of treatment. We report on a systematic literature review, in …


The Use Of Propensity Score Methods With Survival Or Time-To-Event Outcomes: Reporting Measures Of Effect Similar To Those Used In Randomized Experiments, Peter C. Austin Jan 2014

The Use Of Propensity Score Methods With Survival Or Time-To-Event Outcomes: Reporting Measures Of Effect Similar To Those Used In Randomized Experiments, Peter C. Austin

Peter Austin

Propensity score methods are increasingly being used to estimate causal treatment effects in observational studies. In medical and epidemiological studies, outcomes are frequently time-to-event in nature. Propensity-score methods are often applied incorrectly when estimating the effect of treatment on time-to-event outcomes. This article describes how two different propensity score methods (matching and inverse probability of treatment weighting) can be used to estimate the measures of effect that are frequently reported in randomized controlled trials: (i) marginal survival curves, which describe survival in the population if all subjects were treated or if all subjects were untreated; and (ii) marginal hazard ratios. …


The Performance Of Different Propensity Score Methods For Estimating Absolute Effects Of Treatments On Survival Outcomes: A Simulation Study, Peter C. Austin Jan 2014

The Performance Of Different Propensity Score Methods For Estimating Absolute Effects Of Treatments On Survival Outcomes: A Simulation Study, Peter C. Austin

Peter Austin

Observational studies are increasingly being used to estimate the effect of treatments, interventions and exposures on outcomes that can occur over time. Historically, the hazard ratio, which is a relative measure of effect, has been reported. However, medical decision making is best informed when both relative and absolute measures of effect are reported. When outcomes are time-to-event in nature, the effect of treatment can also be quantified as the change in mean or median survival time due to treatment and the absolute reduction in the probability of the occurrence of an event within a specified duration of follow-up. We describe …