Small sample sizes: A big data problem in high-dimensional data analysis.

Abstract:

: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 max t-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 distribution of the maximum statistic. Extensive simulation studies confirm that the new method is particularly suitable for analyzing data sets with small sample sizes. A real data set illustrates the application of the methods.

journal_name

Stat Methods Med Res

authors

Konietschke F,Schwab K,Pauly M

doi

10.1177/0962280220970228

subject

Has Abstract

pub_date

2020-11-24 00:00:00

pages

962280220970228

eissn

0962-2802

issn

1477-0334

pub_type

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