Average Treatment Effect (ATE) Measure
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An Average Treatment Effect (ATE) Measure is a treatment effect measure based on the difference in mean (average) outcomes between units assigned to the treatment and units assigned to the control.
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- See: Observational Study, Mean, Randomized Trial, Estimator, Causal, Statistical Population, Study Design.
References
2022
- (Wikipedia, 2022) ⇒ https://en.wikipedia.org/wiki/Average_treatment_effect Retrieved:2022-8-14.
- 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 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 population) that a researcher desires to know, defined without reference to the study design or estimation procedure. Both observational studies and experimental study designs with random assignment may enable one to estimate an ATE in a variety of ways.
2022
- (Jun et al., 2022) ⇒ Inyoung Jun, Simone Marini, Christina A. Boucher, J. Glenn Morris, Jiang Bian, and Mattia Prosperi. (2022). “Joint Application of the Target Trial Causal Framework and Machine Learning Modeling to Optimize Antibiotic Therapy: Use Case on Acute Bacterial Skin and Skin Structure Infections Due to Methicillin-resistant Staphylococcus Aureus.” arXiv.
- QUOTE: ... Randomized clinical trials provide average treatment effect estimates but are not ideal for risk stratification and optimization of therapeutic choice, i.e., individualized treatment effects (ITE). ...