Cited by 207Statistical Methods in Clinical TrialsStatistical Methods and Bayesian InferenceMeta-analysis and systematic reviews

Comparisons of methods for multiple hypothesis testing in neuropsychological research

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Blakesley, Richard E., Mazumdar, Sati, Dew, Mary Amanda, Houck, Patricia R., Tang, Gong, Reynolds, Charles F., Butters, Meryl A.·2009·Neuropsychology

Abstract

Hypothesis testing with multiple outcomes requires adjustments to control Type I error inflation, which reduces power to detect significant differences. Maintaining the prechosen Type I error level is challenging when outcomes are correlated. This problem concerns many research areas, including neuropsychological research in which multiple, interrelated assessment measures are common. Standard p value adjustment methods include Bonferroni-, Sidak-, and resampling-class methods. In this report, the authors aimed to develop a multiple hypothesis testing strategy to maximize power while controlling Type I error. The authors conducted a sensitivity analysis, using a neuropsychological dataset, to offer a relative comparison of the methods and a simulation study to compare the robustness of the methods with respect to varying patterns and magnitudes of correlation between outcomes. The results lead them to recommend the Hochberg and Hommel methods (step-up modifications of the Bonferroni method) for mildly correlated outcomes and the step-down minP method (a resampling-based method) for highly correlated outcomes. The authors note caveats regarding the implementation of these methods using available software.

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  1. Saltelli A Chan K Scott EM Sensitivity analysis: Gauging the worth of scientific models 2000 New York Wiley
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Authors
Blakesley, R. E., Mazumdar, S., Dew, M. A., Houck, P. R., Tang, G., Reynolds, C. F., & Butters, M. A.
Affiliations
University of Pittsburgh (US)
Venue
Neuropsychology
Published
2009-03
Volume
23
Issue
2
Pages
255-264
ISSN
  • 0894-4105 (ISSN-L)
  • 1931-1559
OpenAlex
W2026344558
Cited by
206
References
18
Citations by year
2026: 14 · 2025: 22 · 2024: 9 · 2023: 13 · 2022: 10 · 2021: 17 · 2020: 16 · 2019: 16 · 2018: 16 · 2017: 21 · 2016: 14 · 2015: 15 · 2014: 8 · 2013: 8 · 2012: 3
FWCI
1.66
Type
journal article
Language
en
Open access
Locations
  • Neuropsychology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institute of Mental Health (T32 MH073451; P30 MH071944; R01 MH072947)
  • National Institute on Aging (P01 AG020677)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords
multiple comparisons, type I error control, statistical power, Bonferroni correction, resampling, correlated outcomes, neuropsychological assessment, sensitivity analysis, simulation study
MeSH terms
Aged, Aged, 80 and over, Data Interpretation, Statistical, Depression, Female, Humans, Male, Middle Aged, Neuropsychological Tests, Research, Models, Statistical, Case-Control Studies

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