Using Large Language Models for Sensitivity Analysis in Causal Inference: Case Studies on Cornfield's Inequality and the E-Value
- DOI
- 10.1353/obs.00013
- Published
- 2026
- Container
- Observational Studies
- Publisher
- Project MUSE
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1353/obs.00013,
title = {Using Large Language Models for Sensitivity Analysis in Causal Inference: Case Studies on Cornfield's Inequality and the E-Value},
author = {Qingyan Xiang and Jiahao Zhang and Bojian Feng},
year = {2026},
journal = {Observational Studies},
doi = {10.1353/obs.00013},
url = {https://doi.org/10.1353/obs.00013}
}RIS
TY - JOUR TI - Using Large Language Models for Sensitivity Analysis in Causal Inference: Case Studies on Cornfield's Inequality and the E-Value AU - Qingyan Xiang AU - Jiahao Zhang AU - Bojian Feng PY - 2026 JO - Observational Studies DO - 10.1353/obs.00013 UR - https://doi.org/10.1353/obs.00013 ER -
APA
Xiang, Q., Zhang, J., & Feng, B. (2026). Using Large Language Models for Sensitivity Analysis in Causal Inference: Case Studies on Cornfield's Inequality and the E-Value. Observational Studies. https://doi.org/10.1353/obs.00013
Source records
- crossref · retrieved 2026-09-25T00:48:44.765Z