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Exact tests via multiple data splitting

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  • DiCiccio, Cyrus J.
  • DiCiccio, Thomas J.
  • Romano, Joseph P.

Abstract

Methods for the construction of hypothesis tests based on multiple data splitting are presented. The tests combine p-values, and exhibit overall Type 1 error control. But, it is also shown that multiple data splitting may have worse power than single splitting.

Suggested Citation

  • DiCiccio, Cyrus J. & DiCiccio, Thomas J. & Romano, Joseph P., 2020. "Exact tests via multiple data splitting," Statistics & Probability Letters, Elsevier, vol. 166(C).
    • Handle: RePEc:eee:stapro:v:166:y:2020:i:c:s0167715220301681
    DOI: 10.1016/j.spl.2020.108865
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    References listed on IDEAS

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    1. Vladimir Vovk & Ruodu Wang, 0. "Combining p-values via averaging," Biometrika, Biometrika Trust, vol. 107(4), pages 791-808.
    2. Meinshausen, Nicolai & Meier, Lukas & Bühlmann, Peter, 2009. "p-Values for High-Dimensional Regression," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1671-1681.
    3. Rubin Daniel & Dudoit Sandrine & van der Laan Mark, 2006. "A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 5(1), pages 1-20, August.
    4. Jianqing Fan & Jinchi Lv, 2008. "Sure independence screening for ultrahigh dimensional feature space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 849-911, November.
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    Citations

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    Cited by:

    1. Solari, Aldo & Djordjilović, Vera, 2022. "Multi split conformal prediction," Statistics & Probability Letters, Elsevier, vol. 184(C).
    2. Choi, Woohyun & Kim, Ilmun, 2023. "Averaging p-values under exchangeability," Statistics & Probability Letters, Elsevier, vol. 194(C).
    3. David M. Ritzwoller & Joseph P. Romano, 2023. "Reproducible Aggregation of Sample-Split Statistics," Papers 2311.14204, arXiv.org, revised Dec 2023.
    4. Cai Yong & Canay Ivan A. & Kim Deborah & Shaikh Azeem M., 2023. "On the Implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 85-103, January.
    5. D García Rasines & G A Young, 2023. "Splitting strategies for post-selection inference," Biometrika, Biometrika Trust, vol. 110(3), pages 597-614.
    6. Brice Ozenne & Esben Budtz-Jørgensen & Sebastian Elgaard Ebert, 2023. "Controlling the familywise error rate when performing multiple comparisons in a linear latent variable model," Computational Statistics, Springer, vol. 38(1), pages 1-23, March.
    7. Andreas Hagemann, 2023. "Inference on quantile processes with a finite number of clusters," Papers 2301.04687, arXiv.org, revised Jun 2023.
    8. Jelle J Goeman & Aldo Solari, 2024. "On selection and conditioning in multiple testing and selective inference," Biometrika, Biometrika Trust, vol. 111(2), pages 393-416.

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