Treatment Effect Heterogeneity
Jeffrey A. Smith
Abstract
This paper considers recent methodological developments in the treatment effects literature, describes their value for applied evaluation work, and suggests next steps. It pays particular attention to documenting the presence of treatment effect heterogeneity, to the quest to attach treatment effect heterogeneity to particular subgroups and other moderators, and to the recent application of machine learning methods in this domain.
Topics & Concepts
Value (mathematics)Treatment effectComputer sciencePsychologyMachine learningMedicineTraditional medicineAdvanced Causal Inference TechniquesHealth Systems, Economic Evaluations, Quality of LifeStatistical Methods and Inference