Some contributions to the analysis of multivariate data

Arne C. Bathke, Solomon W. Harrar, M. Rauf Ahmad

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


In this paper, we provide an overview of recently developed methods for the analysis of multivariate data that do not necessarily emanate from a normal universe. Multivariate data occur naturally in the life sciences and in other research fields. When drawing inference, it is generally recommended to take the multivariate nature of the data into account, and not merely analyze each variable separately. Furthermore, it is often of major interest to select an appropriate set of important variables. We present contributions in three different, but closely related, research areas: first, a general approach to the comparison of mean vectors, which allows for profile analysis and tests of dimensionality; second, non-parametric and parametric methods for the comparison of independent samples of multivariate observations; and third, methods for the situation where the experimental units are observed repeatedly, for example, over time, and the main focus is on analyzing different time profiles when the number p of repeated observations per subject is larger than the number n of subjects.

Original languageEnglish
Pages (from-to)285-303
Number of pages19
JournalBiometrical Journal
Issue number2
StatePublished - Apr 2009


  • ANOVA-type test
  • Bartlett-nanda-pillai test
  • Lawley-hotelling test
  • Likelihood ratio test
  • Repeated measures

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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