# A Multiple-Testing Approach to the Multivariate Behrens-Fisher ProblemIntroduction

A Multiple-Testing Approach to the Multivariate Behrens-Fisher Problem: Introduction [In this chapter, we give a brief introduction to the Behrens–Fisher problem. An outline of the rest of the chapters is also provided. Since randomly incomplete data is considered in the rest of the chapters, we thereafter clarify the idea of “missing at random (MAR)” and “missing completely at random (MCAR).” In particular, we demonstrate that if variables in a data set are all mutually dependent, then an assumption of MAR is equivalent to the assumption of MCAR.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

# A Multiple-Testing Approach to the Multivariate Behrens-Fisher ProblemIntroduction

Part of the SpringerBriefs in Statistics Book Series
Springer Journals — Jan 29, 2013
3 pages

/lp/springer-journals/a-multiple-testing-approach-to-the-multivariate-behrens-fisher-problem-mCVBW00GuD
Publisher
Springer New York
ISBN
978-1-4614-6442-6
Pages
1 –4
DOI
10.1007/978-1-4614-6443-3_1
Publisher site
See Chapter on Publisher Site

### Abstract

[In this chapter, we give a brief introduction to the Behrens–Fisher problem. An outline of the rest of the chapters is also provided. Since randomly incomplete data is considered in the rest of the chapters, we thereafter clarify the idea of “missing at random (MAR)” and “missing completely at random (MCAR).” In particular, we demonstrate that if variables in a data set are all mutually dependent, then an assumption of MAR is equivalent to the assumption of MCAR.]

Published: Jan 29, 2013

Keywords: Behrens–Fisher problem; Missing data; MAR; MCAR; Multivariate; Normality