Categories → Causal Inference , Statistics , Study Design , Causal Effect
Average Treatment Effect on the Treated (ATT) is a concept in causal inference that measures the average effect of a treatment on the individuals who actually received the treatment.
The ATT is a specific type of causal effect, which you might want to measure. ATT stands for "Average effect of Treatment on the Treated" i.e. on the subset of participants or subjects who received the particular intervention or treatment being studied. This is distinct from other causal effects such as the ATE, the Average Treatment Effect [on the entire population studied].
The ATT is used to evaluate the effectiveness of a treatment in a specific population.
For more information about the ATT, see this article.
In the context of a randomized controlled trial, the ATT can be estimated by comparing the outcomes of individuals who received the treatment to the outcomes of individuals who did not receive the treatment, but who were otherwise similar in all relevant respects.
In observational studies, where the assignment of treatment is not random, the ATT can be estimated using methods such as propensity score matching or regression analysis that adjust for confounding factors that may affect both the treatment assignment and the outcome.
The ATT is an important concept in causal inference because it allows researchers to estimate the causal effect of a treatment in a specific population, which is often more relevant for decision-making than the average treatment effect across all individuals in a study (i.e. the Average Treatment Effect, ATE). By focusing on the effect of the treatment on those who actually received it, the ATT can provide more accurate estimates of the effectiveness of the treatment for the population of interest.