In causal mediation analysis, the definitions of the natural direct and indirect effects involve potential outcomes that can never be observed, so-called a priori counterfactuals. This conceptual challenge translates into issues in identification, which requires strong and often unverifiable assumptions, including sequential ignorability. Alternatively, we can deal with post-treatment variables using the principal stratification framework, where causal effects are defined as comparisons of observable potential outcomes. We establish a novel bridge between mediation analysis and principal stratification, which helps to clarify and weaken the commonly-used identifying assumptions for natural direct and indirect effects. Using principal stratification, we show how sequential ignorability extrapolates from observable potential outcomes to a priori counterfactuals, and propose alternative weaker principal ignorability-type assumptions. We illustrate the key concepts using a clinical trial.
Principal ignorability in mediation analysis: through and beyond sequential ignorability / Laura Forastiere, Alessandra Mattei, Peng Ding. - In: BIOMETRIKA. - ISSN 0006-3444. - STAMPA. - 105:(2018), pp. 979-986. [10.1093/biomet/asy053]
Principal ignorability in mediation analysis: through and beyond sequential ignorability
Laura Forastiere
;Alessandra Mattei;
2018
Abstract
In causal mediation analysis, the definitions of the natural direct and indirect effects involve potential outcomes that can never be observed, so-called a priori counterfactuals. This conceptual challenge translates into issues in identification, which requires strong and often unverifiable assumptions, including sequential ignorability. Alternatively, we can deal with post-treatment variables using the principal stratification framework, where causal effects are defined as comparisons of observable potential outcomes. We establish a novel bridge between mediation analysis and principal stratification, which helps to clarify and weaken the commonly-used identifying assumptions for natural direct and indirect effects. Using principal stratification, we show how sequential ignorability extrapolates from observable potential outcomes to a priori counterfactuals, and propose alternative weaker principal ignorability-type assumptions. We illustrate the key concepts using a clinical trial.File | Dimensione | Formato | |
---|---|---|---|
25_FMP_2018.pdf
accesso aperto
Descrizione: Articolo principale
Tipologia:
Pdf editoriale (Version of record)
Licenza:
Open Access
Dimensione
151.32 kB
Formato
Adobe PDF
|
151.32 kB | Adobe PDF |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.