Suppr超能文献

CAHOST:一个用于促进多元回归中双向交互作用的约翰逊 - 奈曼技术的Excel工作簿。

CAHOST: An Excel Workbook for Facilitating the Johnson-Neyman Technique for Two-Way Interactions in Multiple Regression.

作者信息

Carden Stephen W, Holtzman Nicholas S, Strube Michael J

机构信息

Department of Mathematical Sciences, Georgia Southern UniversityStatesboro, GA, United States.

Department of Psychology, Georgia Southern UniversityStatesboro, GA, United States.

出版信息

Front Psychol. 2017 Jul 28;8:1293. doi: 10.3389/fpsyg.2017.01293. eCollection 2017.

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.

摘要

在使用多元回归时,研究人员常常希望探究两个变量之间的关系是如何被另一个变量调节的;这被称为交互作用。从历史上看,有两种方法被用于探究交互作用:选点法和约翰逊 - 奈曼(JN)技术。选点法存在一些局限性,而使用JN技术可以避免这些局限性。目前,可用于实施JN技术并创建相应图形的软件缺乏一些理想的功能——最显著的是易用性和图形质量。为了填补文献中的这一空白,我们提供了一个免费的Microsoft Excel 2013工作簿CAHOST(作者姓氏前两个字母的拼接),它允许用户无缝创建JN技术结果的可用于发表的图形。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7f5/5532434/1ebce06fe327/fpsyg-08-01293-g0001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验