The simplest procedure for investigating the signficance of an interaction is the “pick-a-point” ( Rogosa, 1980), or “simple slopes” ( Aiken and West, 1991) method in which a few values of the moderator are chosen to be fixed, and the significance of X's effect is investigated at those points with a hypothesis test or by constructing a confidence interval. The following sections will describe the JN technique, the underlying mathematics, detail how the workbook operates on a sheet-per-sheet basis, present a brief example, and conclude. Version 1.0 of the workbook may be found in the Supplementary Material accompanying this article, and future releases may be found at. The target audience is researchers without programming experience who wish to probe interactions. This article describes CAHOST (a concatenation of the first two letters of the authors' last names), an implementation of the JN technique in a Microsoft Excel 2013 macro-enabled workbook (.xlsm) which produces high-quality publication-ready graphics, requires no programming capabilities, and limits error in data entry (e.g., entering coefficients). One of the tools used in moderation analysis is the Johnson-Neyman (JN) technique. Taking the view that X is the primary variable of interest or the “focal predictor,” the other explanatory variable M is the “moderator.” Thus, the study of how the explanatory variables interact is often called moderation analysis ( Cohen et al., 2003 Hayes, 2013b). In such a situation, the two explanatory variables are said to “interact” in their influence on the response variable. For example, a person's blood alcohol content is influenced by the amount of alcohol that person has ingested, but the size of this influence depends on, among other things, the body mass of that person. When a researcher seeks to quantify the linear effect an explanatory variable, X, has on a response variable, Y, the size of that effect may depend on a second explanatory variable, M. 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. 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. ![]() ![]() The pick-a-point approach has limitations that can be avoided using the JN technique. Historically, two approaches have been used to probe interactions: the pick-a-point approach and the Johnson-Neyman (JN) technique. 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.
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