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Power enhancement of permutation-augmented partial-correlation tests via fixed-row permutations

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  • Wang, Tianyi
  • Wang, Guanghui
  • Wang, Zhaojun
  • Zou, Changliang

Abstract

Permutation-based partial-correlation tests guarantee finite-sample Type I error control under any fixed design and exchangeable noise, yet their power can collapse when the permutation-augmented design aligns too closely with the covariate of interest. We remedy this by fixing a design-driven subset of rows and permuting only the remainder. The fixed rows are chosen by a greedy algorithm that maximizes a lower bound on power. This strategy reduces covariate-permutation collinearity while preserving worst-case Type I error control. Simulations confirm that this refinement maintains nominal size and delivers substantial power gains over original unrestricted permutations, especially in high-collinearity regimes.

Suggested Citation

  • Wang, Tianyi & Wang, Guanghui & Wang, Zhaojun & Zou, Changliang, 2026. "Power enhancement of permutation-augmented partial-correlation tests via fixed-row permutations," Statistics & Probability Letters, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:stapro:v:230:y:2026:i:c:s0167715225002366
    DOI: 10.1016/j.spl.2025.110591
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