Testing Significance of a Mean Vector - A Possible Alternative to Hotelling's T Squared.

Abstract

In problems involving multivariate measurements experimental considerations often indicate grouping of variables into subsets ordered according to their importance. In such situations, the problems such as comparison of two mean vectors and profile analysis may be treated by Hotelling's T-square-test, adapted along the lines of the step-wise procedure of J. Roy, or the well known test for additional information due to Rao. In this paper, a modification of the step-wise procedure obtained by combining the component tests is studied. The exact Bahadur slopes of resulting procedures are computed and it is shown that the procedure based upon Fisher's combination method is asymptotically equivalent to Hotelling's T-square. A Monte Carlo study suggests that even in small samples the power functions of the new method and Hotelling's T-square-test are practically equivalent.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1977
Accession Number
ADA042644

Entities

People

  • Govind S. Mudholkar
  • Perla Subbaiah

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Biological Processes
  • Data Science
  • Data Sets
  • Governments
  • Information Science
  • Invariance
  • Measurement
  • Normal Distribution
  • Observation
  • Scientific Research
  • Simulations
  • Statistics
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Statistical inference.