Choosing the Causal Estimand for Propensity Score Analysis of Observational Studies

Understand

Matching and weighting methods for observational studies involve the choice of an estimand, the causal effect with reference to a specific target population.

• Commonly used estimands include the average treatment effect in the treated (ATT), the average treatment effect in the untreated (ATU), the average treatment effect in the population (ATE), and the average treatment effect in the overlap (i.e., equipoise population; ATO).
• Each estimand has its own assumptions, interpretation, and statistical methods that can be used to estimate it.
• This article provides guidance on selecting and interpreting an estimand to help medical researchers correctly implement statistical methods used to estimate causal effects in observational studies and to help audiences correctly interpret the results and limitations of these studies.