Computational Statistics

, Volume 25, Issue 1, pp 71–95

Comparing several population means: a parametric bootstrap method, and its comparison with usual ANOVA F test as well as ANOM

  • Ching-Hui Chang
  • Nabendu Pal
  • Wooi Khai Lim
  • Jyh-Jiuan Lin
Original Paper

DOI: 10.1007/s00180-009-0162-z

Cite this article as:
Chang, CH., Pal, N., Lim, W.K. et al. Comput Stat (2010) 25: 71. doi:10.1007/s00180-009-0162-z

Abstract

This paper deals with testing the equality of several homoscedastic normal population means. We introduce a newly developed computational approach test (CAT), which is essentially a parametric bootstrap method, and discuss its merits and demerits. In the process of studying the CAT’s usefulness, we compare it with the traditional one-way ANOVA’s F test as well as the analysis of means (ANOM) method. Further, the model robustness of the above three methods have been studied under the ‘t-model’. The motivation behind the proposed CAT is to provide the applied researchers a statistical tool to carry out a comparison of several population means, in a parametric setup, without worrying about the sampling distribution of the inherent test statistic. The CAT can be used to test the equality of several means when the populations are assumed to be heteroscedastic t-distributions.

Keywords

Comparing means Hypothesis testing Power function Size 

Mathematics Subject Classification (2000)

Primary 62F03 62F25 Secondary 62E17 

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Ching-Hui Chang
    • 1
  • Nabendu Pal
    • 2
  • Wooi Khai Lim
    • 3
  • Jyh-Jiuan Lin
    • 4
  1. 1.Department of Applied Statistics and Information ScienceMing Chuan UniversityTaoyuan CountyTaiwan, ROC
  2. 2.Department of MathematicsUniversity of Louisiana at LafayetteLafayetteUSA
  3. 3.Department of MathematicsWilliam Paterson UniversityWayneUSA
  4. 4.Department of StatisticsTamkang UniversityTamsui, TaipeiTaiwan, ROC

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