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The '''average treatment effect''' ('''ATE''') is a measure used to compare treatments (or interventions) in randomized experiments, evaluation of policy interventions, and medical trials. The ATE measures the difference in [[mean]] (average) outcomes between units assigned to the treatment and units assigned to the control.  In a [[randomized trial]] (i.e., an experimental study), the average treatment effect can be [[Estimator|estimated]] from a sample using a comparison in mean outcomes for treated and untreated units. However, the ATE is generally understood as a [[causal]] parameter (i.e., an estimate or property of a [[Statistical population|population]]) that a researcher desires to know, defined without reference to the [[study design]] or estimation procedure. Both [[Observational study|observational]] studies and experimental study designs with random assignment may enable one to estimate an ATE in a variety of ways.

The '''average treatment effect''' ('''ATE''') is a measure used to compare treatments (or interventions) in randomized experiments, evaluation of policy interventions, and medical trials. The ATE measures the difference in [[mean]] (average) outcomes between units assigned to the treatment and units assigned to the control.  In a [[randomized trial]] (i.e., an experimental study), the average treatment effect can be [[Estimator|estimated]] from a sample using a comparison in mean outcomes for treated and untreated units. However, the ATE is generally understood as a [[causal]] parameter (i.e., an estimate or property of a [[Statistical population|population]]) that a researcher desires to know, defined without reference to the [[study design]] or estimation procedure. Both [[Observational study|observational]] studies and experimental study designs with random assignment may enable one to estimate an ATE in a variety of ways.