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CAHOST Facilitating the Johnson-Neyman Technique for Two-Way Interactions in Multiple Regression
Frontiers in Psychology (2017)
  • Stephen W. Carden, Georgia Southern University
  • Nicholas S. Holtzman, Georgia Southern University
  • Michael J Strube, Washington University in St. Louis
When using multiple regression, researchers frequently wish to explore how the relationship between two variables is moderated by another variable; this is termed an interaction. Historically, two approaches have been used to probe interactions: the pick-a-point approach and the Johnson-Neyman (JN) technique. The pick-a-point
approach has limitations that can be avoided using the JN technique. Currently, the software available for implementing the JN technique and creating corresponding figures lacks several desirable features–most notably, ease of use and figure quality. To fill this gap in the literature, we offer a free Microsoft Excel 2013 workbook, CAHOST (a concatenation of the first two letters of the authors’ last names), that allows the user to seamlessly create publication-ready figures of the results of the JN technique.
  • Moderation,
  • Johnson-Neyman,
  • Interactions,
  • Probing interactions,
  • Multiple regression
Publication Date
July 28, 2017
Publisher Statement

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

This article was originally retrieved from Frontiers in Psychology.
Citation Information
Stephen W. Carden, Nicholas S. Holtzman and Michael J Strube. "CAHOST Facilitating the Johnson-Neyman Technique for Two-Way Interactions in Multiple Regression" Frontiers in Psychology Vol. 8 Iss. 1293 (2017) p. 1 - 7 ISSN: 1664-1078
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