An alternative derivation of aligned rank tests for regression

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

A new method for deriving aligned rank tests and their efficacy is presented. The approach makes use of the asymptotic version of the rank transformation. Under the null hypothesis, the transformed data conform to a linear model and thus an F-test statistic based on the transformed data is easily constructed. Properties of the empirical process are then used to show that the F-statistic based on the rank transformation is asymptotically equivalent to the F-statistic based on the asymptotic version of the rank transformation. This approach has a strong heuristic flavor making it more suitable for classroom presentation.

Original languageEnglish (US)
Pages (from-to)171-186
Number of pages16
JournalJournal of Statistical Planning and Inference
Volume27
Issue number2
DOIs
StatePublished - Jan 1 1991

Fingerprint

Rank Test
F-statistics
Regression
Statistics
Alternatives
F Test
Asymptotically equivalent
Empirical Process
Flavors
Null hypothesis
Test Statistic
Efficacy
Linear Model
Heuristics
Rank test

All Science Journal Classification (ASJC) codes

  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Statistics and Probability

Cite this

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An alternative derivation of aligned rank tests for regression. / Akritas, Michael G.

In: Journal of Statistical Planning and Inference, Vol. 27, No. 2, 01.01.1991, p. 171-186.

Research output: Contribution to journalArticle

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