Abstract
In causal mediation analysis, natural effects are identified only under strict assumptions involving cross-world counterfactuals. An alternative approach recently developed, called separable, allows for identification of mediational effects in a wide range of models, since it relies on weaker assumptions than those required by natural effects. In this paper, the separable-effect approach is revised and an application to data is presented.
Lingua originale | English |
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Titolo della pubblicazione ospite | Book of Short Papers - SIS 2021 |
Pagine | 1382-1387 |
Numero di pagine | 6 |
Stato di pubblicazione | Published - 2021 |