Surrogate outcomes and transportability
Abstract
Identification of causal effects is one of the most fundamental tasks of causal inference. We consider an identifiability problem where some experimental and observational data are available but neither data alone is sufficient for the identification of the causal effect of interest. Instead of the outcome of interest, surrogate outcomes are measured in the experiments. This problem is a generalization of identifiability using surrogate experiments [1] and we label it as surrogate outcome identifiability. We show that the concept of transportability [2] provides a sufficient criteria for determining surrogate outcome identifiability for a large class of queries.
Main Authors
Format
Articles
Research article
Published
2019
Series
Subjects
Publication in research information system
Publisher
Elsevier
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201903121836Use this for linking
Review status
Peer reviewed
ISSN
0888-613X
DOI
https://doi.org/10.1016/j.ijar.2019.02.007
Language
English
Published in
International Journal of Approximate Reasoning
Citation
- Tikka, S., & Karvanen, J. (2019). Surrogate outcomes and transportability. International Journal of Approximate Reasoning, 108. https://doi.org/10.1016/j.ijar.2019.02.007
License
Funder(s)
Research Council of Finland
Funding program(s)
Profilointi, SA
Research profiles, AoF
Additional information about funding
This work belongs to the thematic research area “Decision analytics utilizing causal models and multiobjective optimization” (DEMO) supported by Academy of Finland (grant number 311877). We thank the anonymous reviewers for their comments which helped to substantially improve this paper.
Copyright© 2019 Elsevier Inc.