A note on “Simple graphical rules to assess selection bias in general-population and selected-sample treatment effects” by M. B. Mathur and I. Shpitser

• Stanghellini, Elena ^[1] ; Doretti, Marco ^[2] ; Tezuka, Taiki ^[3]
  1. [1] Università di Perugia

     Università di Perugia

     Perusa, Italia

     
  2. [2] University of Florence

     University of Florence

     Firenze, Italia

     
  3. [3] Yokohama National University

     Yokohama National University

     Naka Ku, Japón

     

  Mostrar afiliaciones +
• Localización: American journal of epidemiology, ISSN-e 1476-6256, ISSN 0002-9262, Vol. 194, Nº. 3, 2025, págs. 562-564
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

  • Abstract This short note is a commentary on a 2024 article by Mathur and Shpitser in the Journal, with the aim to enlarge the class of graphs for which the conditional average treatment effect is nonparametrically identified, by allowing the outcome to be on the pathway between the treatment and the selection indicator. A first straightforward generalization is possible when (1) the outcome $Y$ is binary, and (2) the population prevalence of $Y$ is known a priori or can be made the object of a sensitivity analysis. Furthermore, identification of the effect is possible also for $Y$ having any nature, provided that a selection bias breaking node $V$ exists and the population prevalence of $V$ is known.