Safe hypotheses testing with application to order restricted inference
Ori Davidov

TL;DR
This paper introduces safe hypothesis tests for order-restricted inference that prevent misleading conclusions due to misspecified constraints, ensuring valid inferences with controlled Type III errors.
Contribution
It proposes a novel pre-test approach that certifies the validity of hypotheses before testing, enhancing inference reliability in order-restricted problems.
Findings
Strong protection against Type III errors in simulations
Maintains power comparable to standard tests
Applicable beyond order-restricted inference
Abstract
Hypothesis tests under order restrictions arise in a wide range of scientific applications. By exploiting inequality constraints, such tests can achieve substantial gains in power and interpretability. However, these gains come at a cost: when the imposed constraints are misspecified, the resulting inferences may be misleading or even invalid, and Type III errors may occur, i.e., the null hypothesis may be rejected when neither the null nor the alternative is true. To address this problem, this paper introduces safe tests. Heuristically, a safe test is a testing procedure that is asymptotically free of Type III errors. The proposed test is accompanied by a certificate of validity, a pre--test that assesses whether the original hypotheses are consistent with the data, thereby ensuring that the null hypothesis is rejected only when warranted, enabling principled inference without risk of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStatistical Methods in Clinical Trials · Distributed Sensor Networks and Detection Algorithms · SARS-CoV-2 detection and testing
