Why Are We Weighting? Understanding the Estimates From Propensity Score Weighting and Matching Methods.

While the multivariable Cox regression, 1:1 propensity matching, and IPW treatment effect in the treated estimates demonstrate that BIMA was associated with a statistically significantly decreased risk of mortality, the IPW treatment effect in the average study population showed an increased risk of mortality associated with BIMA that was not statistically significant. This is attributed to the different populations (weighted to look like the overall study population versus treated group) represented by the 2 IPW approaches. Determining how the study population is balanced is a large driver of the treatment effect. Ultimately, the treatment effect estimate desired should drive the choice of the propensity score method.