Web: http://arxiv.org/abs/2203.12808

May 5, 2022, 1:11 a.m. | Zijian Guo, Peter Bühlmann

stat.ML updates on arXiv.org arxiv.org

Instrumental variables regression is a popular causal inference method for
endogenous treatment. A significant concern in practical applications is the
validity and strength of instrumental variables. This paper aims to perform
causal inference when all instruments are possibly invalid. To do this, we
propose a novel methodology called two stage curvature identification (TSCI)
together with a generalized concept to measure the strengths of possibly
invalid instruments: such invalid instruments can still be used for inference
in our framework. We fit …

arxiv causal inference identification inference learning machine machine learning stage

More from arxiv.org / stat.ML updates on arXiv.org

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC

Senior Data Science Writer

@ NannyML | Remote