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Controlling Error in Multiple Comparisons, with Examples from State-to-State Differences in Educational Achievement

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  • Valerie S. L. Williams
  • Lyle V. Jones
  • John W. Tukey

Abstract

Three alternative procedures to adjust significance levels for multiplicity are the traditional Bonferroni technique, a sequential Bonferroni technique developed by Hochberg (1988) , and a sequential approach for controlling the false discovery rate proposed by Benjamini and Hochberg (1995). These procedures are illustrated and compared using examples from the National Assessment of Educational Progress (NAEP). A prominent advantage of the Benjamini and Hochberg (B-H) procedure, as demonstrated in these examples, is the greater invariance of statistical significance for given comparisons over alternative family sizes. Simulation studies show that all three procedures maintain a false discovery rate bounded above, often grossly, by α (or α/2). For both uncorrelated and pairwise families of comparisons, the B-H technique is shown to have greater power than the Hochberg or Bonferroni procedures, and its power remains relatively stable as the number of comparisons becomes large, giving it an increasing advantage when many comparisons are involved. We recommend that results from NAEP State Assessments be reported using the B-H technique rather than the Bonferroni procedure.

Suggested Citation

  • Valerie S. L. Williams & Lyle V. Jones & John W. Tukey, 1999. "Controlling Error in Multiple Comparisons, with Examples from State-to-State Differences in Educational Achievement," Journal of Educational and Behavioral Statistics, , vol. 24(1), pages 42-69, March.
    • Handle: RePEc:sae:jedbes:v:24:y:1999:i:1:p:42-69
    DOI: 10.3102/10769986024001042
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    Cited by:

    1. David Afshartous & Michael Wolf, 2007. "Avoiding ‘data snooping’ in multilevel and mixed effects models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 1035-1059, October.
    2. Tangney, June P. & Folk, Johanna B. & Graham, David M. & Stuewig, Jeffrey B. & Blalock, Daniel V. & Salatino, Andrew & Blasko, Brandy L. & Moore, Kelly E., 2016. "Changes in inmates' substance use and dependence from pre-incarceration to one year post-release," Journal of Criminal Justice, Elsevier, vol. 46(C), pages 228-238.
    3. A. Stewart Fotheringham & Taylor M. Oshan, 2016. "Geographically weighted regression and multicollinearity: dispelling the myth," Journal of Geographical Systems, Springer, vol. 18(4), pages 303-329, October.
    4. Omotilewa, Oluwatoba J. & Ricker-Gilbert, Jacob & Ainembabazi, John Herbert & Shively, Gerald E., 2018. "Does improved storage technology promote modern input use and food security? Evidence from a randomized trial in Uganda," Journal of Development Economics, Elsevier, vol. 135(C), pages 176-198.

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