What does this research mean for the field?

The Sum Max-Component (SMC) test is an effective statistical method for one-sided high-dimensional mean vector testing, demonstrating competitive type I error and power rates for applications such as gene set enrichment analysis. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This research aims to develop and validate a new method for one-sided testing of high-dimensional mean vectors.

May 31, 2026Biostatistics

High-dimensional test for one-sided hypotheses

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This research aims to develop and validate a new method for one-sided testing of high-dimensional mean vectors.
Developed the Sum Max-Component (SMC) test for one-sided hypotheses.
Examined the asymptotic behavior of the SMC test in high-dimensional data.
Validated the SMC test using proteomic data from ovarian cancer patients.
The SMC test shows competitive type I error rates and power in finite samples.
Successfully applied the SMC test in gene set enrichment analysis for ovarian cancer.
Demonstrated effectiveness in detecting up-regulated gene sets in the studied data.

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Implication

Randomized trial examines the SMC test's effectiveness in gene set analysis, indicating its potential in ovarian cancer research.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/6a1bd0fa5783ba022b6fca70 https://doi.org/10.1093/biostatistics/kxag016

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High-dimensional test for one-sided hypotheses

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Implication

Cite This Study

High-dimensional test for one-sided hypotheses

Key Points

Discussion

Implication

Cite This Study

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