A Monte-Carlo simulation package, multiple comparison corrections and power estimation incorporating secondary supportive evidence

K. Chen, E. M. Reiman, Gene E Alexander

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Various approaches have been proposed to account for the family-wise type-I errors in neuroimaging studies. This study introduces new global features as alternatives to address the multiple-comparison issue. These global features can serve as alternative brain indices whose type-I error theoretical calculations are unknown. A Monte-Carlo simulation package was used to calculate the family-wise type-I error of the newly introduced global features, as well as the conventional multiple comparison corrected p-values related to the height of the statistic (and cluster size) of interest in situations where random field theorem based p-values might be validated. In addition, this package was designed to perform statistical power analyses, taking multiple comparisons into consideration for the conventional statistics and the new global features. The behaviors of the global index type-I error thresholds as a function of the degrees of freedom (D) of t-distribution were investigated. Data from an oxygen-15 water PET study of right hand movement was used to illustrate the use of the global features and their type-I error and statistical power. With this PET example, we showed the superior statistical power of some global indices in cases where there were moderate changes over a relatively large brain volume. We believe that the global features and the calculation of type-I errors/statistical powers by the computer simulation package provide researchers alternative ways to account for multiple comparisons in neuroimaging studies.

Original languageEnglish (US)
Title of host publication2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007
Pages907-913
Number of pages7
DOIs
StatePublished - 2007
Event2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007 - Beijing, China
Duration: May 23 2007May 27 2007

Other

Other2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007
CountryChina
CityBeijing
Period5/23/075/27/07

Fingerprint

Neuroimaging
Brain
Computer Simulation
Hand
Research Personnel
Oxygen
Water
Statistics
Power (Psychology)
Monte Carlo simulation
Computer simulation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Medicine(all)

Cite this

Chen, K., Reiman, E. M., & Alexander, G. E. (2007). A Monte-Carlo simulation package, multiple comparison corrections and power estimation incorporating secondary supportive evidence. In 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007 (pp. 907-913). [4381872] https://doi.org/10.1109/ICCME.2007.4381872

A Monte-Carlo simulation package, multiple comparison corrections and power estimation incorporating secondary supportive evidence. / Chen, K.; Reiman, E. M.; Alexander, Gene E.

2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007. 2007. p. 907-913 4381872.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, K, Reiman, EM & Alexander, GE 2007, A Monte-Carlo simulation package, multiple comparison corrections and power estimation incorporating secondary supportive evidence. in 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007., 4381872, pp. 907-913, 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007, Beijing, China, 5/23/07. https://doi.org/10.1109/ICCME.2007.4381872
Chen K, Reiman EM, Alexander GE. A Monte-Carlo simulation package, multiple comparison corrections and power estimation incorporating secondary supportive evidence. In 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007. 2007. p. 907-913. 4381872 https://doi.org/10.1109/ICCME.2007.4381872
Chen, K. ; Reiman, E. M. ; Alexander, Gene E. / A Monte-Carlo simulation package, multiple comparison corrections and power estimation incorporating secondary supportive evidence. 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007. 2007. pp. 907-913
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