Small sample sizes: A big data problem in high-dimensional data analysis.
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ABSTRACT:
SUBMITTER: Konietschke F
PROVIDER: S-EPMC8008424 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature
Publications
Small sample sizes: A big data problem in high-dimensional data analysis.
Konietschke Frank F Schwab Karima K Pauly Markus M
Statistical methods in medical research 20201124 3
In many experiments and especially in translational and preclinical research, sample sizes are (very) small. In addition, data designs are often high dimensional, i.e. more dependent than independent replications of the trial are observed. The present paper discusses the applicability of <i>max t</i>-test-type statistics (multiple contrast tests) in high-dimensional designs (repeated measures or multivariate) with small sample sizes. A randomization-based approach is developed to approximate the ...[more]
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