Controlling for Multiplicity, Eligibility, and Exclusions

  • Amber SalterEmail author
  • J. Philip Miller
Living reference work entry


Multiple comparison procedures play an important role in controlling the accuracy of clinical trial results while trial eligibility and exclusions have the potential to introduce bias and reduce external validity. This chapter introduces the issues and sources of multiplicity and provides a description of the many different procedures that can be used to address multiplicity primarily used in the confirmatory clinical trial setting. Additionally, trial inclusion/exclusion criteria and enrichment strategies are reviewed.


Multiple comparison procedures Inclusion/exclusion criteria Enrichment strategies 


  1. Dmitrienko A, D’Agostino R (2013) Traditional multiplicity adjustment methods in clinical trials. Stat Med 32(29):5172–5218. Scholar
  2. Dmitrienko A, D’Agostino RB (2018) Multiplicity considerations in clinical trials. N Engl J Med 378(22):2115–2122. Scholar
  3. Dmitrienko A, D’Agostino RB Sr, Huque MF (2013) Key multiplicity issues in clinical drug development. Stat Med 32(7):1079–1111. Scholar
  4. Dunn OJ (1961) Multiple comparisons among means. J Am Stat Assoc 56(293):52–64. Scholar
  5. Dunnett CW (1955) A multiple comparison procedure for comparing several treatments with a control. J Am Stat Assoc 50(272):1096–1121. Scholar
  6. EMA (European MedicinesAgency) (2017) Guideline on multiplicity issues in clinical trials. Retrieved from
  7. FDA (U.S. Food and Drug Administration) (2017) Multiple endpoints in clinical trials: guidance for industry. Retrieved from
  8. Gamble C, Krishan A, Stocken D, Lewis S, Juszczak E, Doré C, … Loder E (2017) Guidelines for the content of statistical analysis plans in clinical trials. JAMA 318(23): 2337. Scholar
  9. Haussig S, Mangner N, Dwyer MG, Lehmkuhl L, Lücke C, Woitek F, … Linke A (2016). Effect of a cerebral protection device on brain lesions following transcatheter aortic valve implantation in patients with severe aortic stenosis. JAMA 316(6): 592. Scholar
  10. Hochberg Y (1988) A sharper Bonferroni procedure for multiple tests of significance. Biometrika 75(4):800–802. Scholar
  11. Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6(2):65–70. Retrieved from Scholar
  12. Hommel G (1988) A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika 75(2):383–386. Scholar
  13. Mehrotra DV, Heyse JF (2004) Use of the false discovery rate for evaluating clinical safety data. Stat Methods Med Res 13(3):227–238. Scholar
  14. Meltzer HY, Cucchiaro J, Silva R, Ogasa M, Phillips D, Xu J, … Loebel A (2011) Lurasidone in the treatment of schizophrenia: a randomized, double-blind, placebo- and olanzapine-controlled study. Am J Psychiatry 168(9): 957–967. Scholar
  15. Proschan MA, Waclawiw MA (2000) Practical guidelines for multiplicity adjustment in clinical trials. Control Clin Trials 21(6):527–539. Scholar
  16. Rothwell PM (2005) External validity of randomised controlled trials: “to whom do the results of this trial apply?”. Lancet 365(9453):82–93. Scholar
  17. Šidák Z (1967) Rectangular confidence regions for the means of multivariate normal distributions. J Am Stat Assoc 62(318):626–633. Scholar
  18. Simes RJ (1986) An improved Bonferroni procedure for multiple tests of significance. Biometrika 73(3):751–754. Scholar
  19. Wiens BL (2003) A fixed sequence Bonferroni procedure for testing multiple endpoints. Pharm Stat 2(3):211–215. Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Division of BiostatisticsWashington University School of Medicine in St. LouisSt. LouisUSA

Section editors and affiliations

  • O. Dale Williams
    • 1
  1. 1.Department of MedicineUniversity of AlabamaBirminghamUSA

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