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On the optimally weighted z-test for combining probabilities from independent studies

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  • Chen, Zhongxue
  • Nadarajah, Saralees

Abstract

Researchers have shown that the optimally weighted z-test, where the weights are the standardized expected difference in means, is more powerful than other methods when combining p-values from independent studies. However, in practice the effect for each independent study is usually unknown, which makes the optimally weighted z-test not applicable. A new test similar to the optimally weighted z-test, but with the effects being estimated from data, is derived. This new test is another generalized Fisher test which can be very powerful under certain situations. The new test is compared with existing methods through simulated data. Some suggestions for choosing tests to combine p-values from independent studies are given. The use of the new test is also illustrated by a real data application.

Suggested Citation

  • Chen, Zhongxue & Nadarajah, Saralees, 2014. "On the optimally weighted z-test for combining probabilities from independent studies," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 387-394.
    • Handle: RePEc:eee:csdana:v:70:y:2014:i:c:p:387-394
    DOI: 10.1016/j.csda.2013.09.005
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    References listed on IDEAS

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    1. Chen, Zhongxue, 2013. "Association tests through combining p-values for case control genome-wide association studies," Statistics & Probability Letters, Elsevier, vol. 83(8), pages 1854-1862.
    2. Loughin, Thomas M., 2004. "A systematic comparison of methods for combining p-values from independent tests," Computational Statistics & Data Analysis, Elsevier, vol. 47(3), pages 467-485, October.
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    Cited by:

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    2. Gelio Alves & Yi-Kuo Yu, 2014. "Accuracy Evaluation of the Unified P-Value from Combining Correlated P-Values," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-11, March.
    3. Hong Zhang & Zheyang Wu, 2023. "The generalized Fisher's combination and accurate p‐value calculation under dependence," Biometrics, The International Biometric Society, vol. 79(2), pages 1159-1172, June.
    4. Chien Li-Chu, 2020. "Combining dependent p-values by gamma distributions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 19(4-6), pages 1-12, December.
    5. Chen Zhongxue & Han Shizhong & Wang Kai, 2017. "Genetic association test based on principal component analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(3), pages 189-198, August.
    6. Ashes Banerjee & Srinivas Pasupuleti & Mritunjay Kumar Singh & G.N. Pradeep Kumar, 2018. "An Investigation of Parallel Post-Laminar Flow through Coarse Granular Porous Media with the Wilkins Equation," Energies, MDPI, vol. 11(2), pages 1-19, February.

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