Flexible template matching for observational study design

• Published in: Statistics in medicine Vol. 42; no. 11; pp. 1760 - 1778
• Main Authors: Zhao, Ruochen, Lu, Bo
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 20.05.2023; Wiley Subscription Services, Inc
• Subjects: Algorithms; attributable effect; average treatment effect; Biomedical Research; Causality; Humans; Observational studies; Observational Studies as Topic; poly‐matching; Research Design; Sample Size; sensitivity analysis; template matching; attributable effect; template matching; average treatment effect; poly-matching; sensitivity analysis

Matching is a popular design for inferring causal effect with observational data. Unlike model‐based approaches, it is a nonparametric method to group treated and control subjects with similar characteristics together, hence to re‐create a randomization‐like scenario. The application of matched desi...