The Annals of Statistics

A Non-Parametric Test of Whether Two Simple Regression Lines are Parallel

Richard F. Potthoff

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Abstract

This paper provides a means for testing the hypothesis that two simple regression lines are parallel, when the two sets of error terms have two arbitrary unknown continuous distributions. The non-parametric test which is developed here is analogous to the two-sample Wilcoxon test. At the end of the paper, two additional problems in non-parametric regression analysis are briefly referred to.

Article information

Source
Ann. Statist., Volume 2, Number 2 (1974), 295-310.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176342664

Digital Object Identifier
doi:10.1214/aos/1176342664

Mathematical Reviews number (MathSciNet)
MR362692

Zentralblatt MATH identifier
0277.62054

JSTOR
links.jstor.org

Subjects
Primary: 62G10: Hypothesis testing
Secondary: 62J05: Linear regression 62G15: Tolerance and confidence regions

Keywords
Non-parametric test parallelism Wilcoxon-Mann-Whitney test simple regression $U$-statistics

Citation

Potthoff, Richard F. A Non-Parametric Test of Whether Two Simple Regression Lines are Parallel. Ann. Statist. 2 (1974), no. 2, 295--310. doi:10.1214/aos/1176342664. https://projecteuclid.org/euclid.aos/1176342664


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