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Determining sample size for cross-over designs with multiple groups

Title
Determining sample size for cross-over designs with multiple groups
Authors
Jo Y.Lee H.Kwon O.Park T.
Ewha Authors
권오란
SCOPUS Author ID
권오란scopus
Issue Date
2018
Journal Title
International Journal of Data Mining and Bioinformatics
ISSN
1748-5673JCR Link
Citation
International Journal of Data Mining and Bioinformatics vol. 20, no. 1, pp. 36 - 46
Keywords
Bonferroni correctionCross-over designsFDRLinear mixed modelSample size calculation
Publisher
Inderscience Enterprises Ltd.
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Conference Paper
Abstract
In clinical research, determining sample size plays an important role. A cross-over design (CD) is widely used to compare multiple groups in order to verify the statistical significance of mean difference among multiple groups, because it has an advantage of removing any factors caused by subject variability. When multi-omics data such as metabolomics data is analysed, we often adopt CD to identify biomarkers that have group effects. While some methods exist for determining the sample size when comparing two groups, no available method allows comparison of more than two treatment groups. In this research, we propose a novel method for determining the sample size of CD with multiple treatment groups. We first propose a method for testing single biomarkers and then a method for a large number of biomarkers while controlling the false discovery rate or the family wise error rate. Copyright © 2018 Inderscience Enterprises Ltd.
DOI
10.1504/IJDMB.2018.092157
Appears in Collections:
신산업융합대학 > 식품영양학과 > Journal papers
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