A multiple testing procedure to proteomic biomarker for disease status
When hundreds of hypotheses are tested simultaneously, the chance of false positives is greatly increased. The article first removed the proteins that contain more than 5 missing values for the active group and 11 for the inactive group. Applying the random seed = 20 and 1,000 bootstrap iterations t...
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Veröffentlicht in: | Canadian journal of statistics 2011-06, Vol.39 (2), p.208-209 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | When hundreds of hypotheses are tested simultaneously, the chance of false positives is greatly increased. The article first removed the proteins that contain more than 5 missing values for the active group and 11 for the inactive group. Applying the random seed = 20 and 1,000 bootstrap iterations to the imputed data, the article found that the results from the four imputation methods are similar and they agree with those without imputation. The results from the multiple testing procedures before the imputation agree more or less with those after the imputation. The reason for this is unclear, it could mean either that the imputation works very well or that it is not very helpful. There is no evidence that race, sex or age is associated with disease status. |
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ISSN: | 0319-5724 1708-945X |
DOI: | 10.1002/cjs |