Open Access. Powered by Scholars. Published by Universities.®

Biostatistics Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 2 of 2

Full-Text Articles in Biostatistics

Statistical Power In Parallel Group Point Exposure Studies With Time-To-Event Outcomes: An Empirical Comparison Of The Performance Of Randomized Controlled Trials And The Inverse Probability Of Treatment Weighting (Iptw) Approach, Peter Austin, Tibor Schuster, Robert W. Platt Jan 2015

Statistical Power In Parallel Group Point Exposure Studies With Time-To-Event Outcomes: An Empirical Comparison Of The Performance Of Randomized Controlled Trials And The Inverse Probability Of Treatment Weighting (Iptw) Approach, Peter Austin, Tibor Schuster, Robert W. Platt

Peter Austin

Background: Estimating statistical power is an important component of the design of both randomized controlled trials (RCTs) and observational studies. Methods for estimating statistical power in RCTs have been well described and can be implemented simply. In observational studies, statistical methods must be used to remove the effects of confounding that can occur due to non-random treatment assignment. Inverse probability of treatment weighting (IPTW) using the propensity score is an attractive method for estimating the effects of treatment using observational data. However, sample size and power calculations have not been adequately described for these methods.

Methods: We used an extensive …


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 …