Document Type
Article
Publication Date
7-28-2017
Publication Title
Frontiers in Psychology
DOI
10.3389/fpsyg.2017.01293
ISSN
1664-1078
Abstract
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.
Recommended Citation
Carden, Stephen W., Nicholas Holtzman, Michael Strube.
2017.
"CAHOST Facilitating the Johnson-Neyman Technique for Two-Way Interactions in Multiple Regression."
Frontiers in Psychology, 8 (1293): 1-7.
doi: 10.3389/fpsyg.2017.01293
https://digitalcommons.georgiasouthern.edu/math-sci-facpubs/472
Excel Workbook
Comments
Copyright © 2017 Carden, Holtzman and Strube. 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.