Informing power and sample size calculations when using inverse probability of treatment weighting using the propensity score.

ABSTRACT: Propensity score weighting is increasingly being used in observational studies to estimate the effects of treatments. The use of such weights induces a within-person homogeneity in outcomes that must be accounted for when estimating the variance of the estimated treatment effect. Knowledge of the variance inflation factor (VIF), which describes the extent to which the effective sample size has been reduced by weighting, allows for conducting sample size and power calculations for observational studies that use propensity score weighting. However, estimation of the VIF requires knowledge of the weights, which are only known once the study has been conducted. We describe methods to estimate the VIF based on two characteristics of the observational study: the anticipated prevalence of treatme

SUBMITTER: Austin PC 

PROVIDER: S-EPMC9293235 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature