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Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate

Author

Listed:
  • Stange, Jens
  • Dickhaus, Thorsten
  • Navarro, Arcadi
  • Schunk, Daniel

Abstract

Under the multiple testing framework, we propose the multiplicity- and dependency-adjustment method (MADAM) which transforms test statistics into adjusted p-values for control of the family-wise error rate. For demonstration, we apply the MADAM to data from a genetic association study.

Suggested Citation

  • Stange, Jens & Dickhaus, Thorsten & Navarro, Arcadi & Schunk, Daniel, 2016. "Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 32-40.
    • Handle: RePEc:eee:stapro:v:111:y:2016:i:c:p:32-40
    DOI: 10.1016/j.spl.2016.01.005
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    References listed on IDEAS

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    1. Dickhaus Thorsten & Straßburger Klaus & Schunk Daniel & Morcillo-Suarez Carlos & Illig Thomas & Navarro Arcadi, 2012. "How to analyze many contingency tables simultaneously in genetic association studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-33, July.
    2. Stange, Jens & Dickhaus, Thorsten & Navarro, Arcadi & Schunk, Daniel, 2016. "Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 32-40.
    3. Jens Stange & Taras Bodnar & Thorsten Dickhaus, 2015. "Uncertainty quantification for the family-wise error rate in multivariate copula models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 281-310, July.
    4. repec:hum:wpaper:sfb649dp2012-049 is not listed on IDEAS
    5. Joseph P. Romano & Michael Wolf, 2005. "Exact and Approximate Stepdown Methods for Multiple Hypothesis Testing," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 94-108, March.
    6. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
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    1. Stange, Jens & Dickhaus, Thorsten & Navarro, Arcadi & Schunk, Daniel, 2016. "Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 32-40.
    2. Anh-Tuan Hoang & Thorsten Dickhaus, 2022. "On the usage of randomized p-values in the Schweder–Spjøtvoll estimator," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 289-319, April.

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