Sequential Test for Practical Significance: Truncated Mixture Sequential Probability Ratio Test

Fuente: arXiv
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Autor principal: Shim, Kyu Min
Formato: Preprint
Publicado: 2025
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author Shim, Kyu Min
author_facet Shim, Kyu Min
contents We present a sequential testing method to identify a practically significant effect. We build on the existing mixture sequential probability ratio test (mSPRT) that can sequentially test for a non-zero treatment effect by using a truncated mixing distribution to differentiate between effects that are large enough to merit a real world action versus that are non-zero but too small to merit a real world action. We verify the Type-I error control of our method theoretically and empirically. We also extend this idea to sequentially test for one-sided practical significance such as non-inferiority testing, and show that we may still effectively control the Type-I error rate.
format Preprint
id arxiv_https___arxiv_org_abs_2509_07892
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Sequential Test for Practical Significance: Truncated Mixture Sequential Probability Ratio Test
Shim, Kyu Min
Methodology
We present a sequential testing method to identify a practically significant effect. We build on the existing mixture sequential probability ratio test (mSPRT) that can sequentially test for a non-zero treatment effect by using a truncated mixing distribution to differentiate between effects that are large enough to merit a real world action versus that are non-zero but too small to merit a real world action. We verify the Type-I error control of our method theoretically and empirically. We also extend this idea to sequentially test for one-sided practical significance such as non-inferiority testing, and show that we may still effectively control the Type-I error rate.
title Sequential Test for Practical Significance: Truncated Mixture Sequential Probability Ratio Test
topic Methodology
url https://arxiv.org/abs/2509.07892