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A comparison of multiple testing adjustment methods with block-correlation positively-dependent tests
In high dimensional data analysis (such as gene expression, spatial epidemiology, or brain imaging studies), we often test thousands or more hypotheses simultaneously. As the number of tests increases, the chance of observing some statistically significant tests is very high even when all null hypot...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5409054/ https://www.ncbi.nlm.nih.gov/pubmed/28453517 http://dx.doi.org/10.1371/journal.pone.0176124 |