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Statistical Guideline #7 Adjust Type 1 Error in Multiple Testing

Abstract

This is one in a series of statistical guidelines designed to highlight common statistical considerations in behavioral medicine research. The goal is to briefly discuss appropriate ways to analyze and present data in the International Journal of Behavioral Medicine (IJBM). Collectively, the series will culminate in a set of basic statistical guidelines to be adopted by IJBM and integrated into the journal’s official instructions for authors, and to serve as an independent resource. If you have ideas for a future topic, please email the Statistical Editor, Ren Liu at rliu45@ucmerced.edu.

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References

  1. Fisher R. A. The design of experiments. Oliver and Boyd. 1935.

  2. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a new and powerful approach to multiple testing. J Roy Stat Soc B. 1995;57:1289–300.

    Google Scholar 

  3. Šidák Z. Rectangular confidence regions for the means of multivariate normal distributions. J Am Stat Assoc. 1967;62:626–33.

    Google Scholar 

  4. Holm S. A simple sequentially rejective multiple test procedure. Scand J Stat. 1979;6:65–70.

    Google Scholar 

  5. Hochberg Y. A sharper Bonferroni procedure for multiple tests of significance. Biometrika. 1988;75:800–2.

    Article  Google Scholar 

  6. Tukey J. W. The problem of multiple comparisons. [Mimeographed Notes] Princeton, NJ: Princeton University. 1953.

  7. Dunnett CW. A multiple comparison procedure for comparing several treatments with a control. J Am Stat Assoc. 1955;50:1096–121.

    Article  Google Scholar 

  8. Hsu JC. Multiple comparisons: theory and methods. Chapman and Hall. 1996.

    Book  Google Scholar 

  9. Segerstrom SC. Statistical guideline #2: report appropriate reliability for your sample, measure, and design. Int J Behav Med. 2019;26:455–6.

    Article  Google Scholar 

  10. Westfall P. H, Lin Y, Young S. Resampling-based multiple testing. Proceedings of the Fifteenth Annual SAS Users Group International. Cary, NC: SAS Institute, Inc., 1990;1359–1364.

  11. Westfall PH, Tobias R, Rom D, Wolfinger R, Hochberg Y. Multiple comparisons and multiple tests using SAS. Cary, NC: SAS Institute Inc; 1999.

    Google Scholar 

  12. Westfall PH, Young SS. Resampling-based multiple testing: examples and methods for p-value adjustment. John Wiley & Sons; 1993.

    Google Scholar 

  13. Cui X, Dickhaus T, Ding Y, Hsu JC. Handbook of multiple comparisons. Routledge; 2021.

    Book  Google Scholar 

  14. Gelman A, Tuerlinckx F. Type S error rates for classical and Bayesian single and multiple comparison procedures. Columbia University Working Paper. Columbia University. 2000.

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Correspondence to Ren Liu.

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Liu, R. Statistical Guideline #7 Adjust Type 1 Error in Multiple Testing. Int.J. Behav. Med. 29, 137–140 (2022). https://doi.org/10.1007/s12529-022-10070-0

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  • DOI: https://doi.org/10.1007/s12529-022-10070-0

Keywords

  • Multiple testing
  • Type 1 error
  • Bootstrap
  • Bonferroni
  • Power
  • p-value
  • α value