Determining sample size for cross-over designs with multiple groups

Yongjun Jo, Hyojin Lee, Oran Kwon, Taesung Park

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

Original languageEnglish
Pages (from-to)36-46
Number of pages11
JournalInternational Journal of Data Mining and Bioinformatics
Issue number1
StatePublished - 2018

Bibliographical note

Funding Information:
This work was supported by the Bio-Synergy Research Project (2013M3A9C4078158) of the Ministry of Science, ICT and Future Planning through the National Research Foundation.

Publisher Copyright:
Copyright © 2018 Inderscience Enterprises Ltd.


  • Bonferroni correction
  • Cross-over designs
  • FDR
  • Linear mixed model
  • Sample size calculation


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