Choosing an estimand for weighted observational studies using design sensitivity

Music City Center 

Choices about observational study design, notably the choice of estimand, have important implications for whether the final estimate will exhibit robustness to unmeasured confounding. In practice however, the aspects of a study that influence sensitivity to unmeasured confounding are not well understood or accounted for when planning a study. We demonstrate how design sensitivity, a quantity describing the asymptotic power of a sensitivity analysis, can be used to compare multiple candidate estimands in weighted observational studies to improve robustness to unmeasured bias. Specifically, using data from a referendum on the 2016 Colombian peace agreement we explore how altering the definition of treatment and altering the target population of interest impact the expected performance of sensitivity analyses.

sensitivity analysis

weighting

estimands

confounding

study design

robust