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Global hypothesis testing for high-dimensional repeated measures outcomes
High-throughput technology in metabolomics, genomics, and proteomics gives rise to high dimension, low sample size data when the number of metabolites, genes, or proteins exceeds the sample size. For a limited class of designs, the classic ‘univariate approach’ for Gaussian repeated measures can pro...
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| Main Authors: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2011
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3396026/ https://ncbi.nlm.nih.gov/pubmed/22161561 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.4435 |
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