Identification and Estimation of Causal Effects Defined by Shift Interventions.

ABSTRACT: Causal inference quantifies cause effect relationships by means of counterfactual responses had some variable been artificially set to a constant. A more refined notion of manipulation, where a variable is artificially set to a fixed function of its natural value is also of interest in particular domains. Examples include increases in financial aid, changes in drug dosing, and modifying length of stay in a hospital. We define counterfactual responses to manipulations of this type, which we call shift interventions. We show that in the presence of multiple variables being manipulated, two types of shift interventions are possible. Shift interventions on the treated (SITs) are defined with respect to natural values, and are connected to effects of treatment on the treated. Shift intervention

SUBMITTER: Sani N 

PROVIDER: S-EPMC7716622 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature