Cortina Jose M, Sheng Zitong, Keener Sheila K, Keeler Kathleen R, Grubb Leah K, Schmitt Neal, Tonidandel Scott, Summerville Karoline M, Heggestad Eric D, Banks George C
Department of Management and Entrepreneurship, Virginia Commonwealth University.
Future of Work Institute, Curtin University.
J Appl Psychol. 2020 Dec;105(12):1351-1381. doi: 10.1037/apl0000815. Epub 2020 Aug 10.
The psychometric soundness of measures has been a central concern of articles published in the Journal of Applied Psychology (JAP) since the inception of the journal. At the same time, it isn't clear that investigators and reviewers prioritize psychometric soundness to a degree that would allow one to have sufficient confidence in conclusions regarding constructs. The purposes of the present article are to (a) examine current scale development and evaluation practices in JAP; (b) compare these practices to recommended practices, previous practices, and practices in other journals; and (c) use these comparisons to make recommendations for reviewers, editors, and investigators regarding the creation and evaluation of measures including Excel-based calculators for various indices. Finally, given that model complexity appears to have increased the need for short scales, we offer a user-friendly R Shiny app (https://orgscience.uncc.edu/about-us/resources) that identifies the subset of items that maximize a variety of psychometric criteria rather than merely maximizing alpha. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
自《应用心理学杂志》（JAP）创刊以来，测量方法的心理测量稳健性一直是该杂志发表文章的核心关注点。与此同时，尚不清楚研究者和审稿人是否将心理测量稳健性置于足够的优先地位，以使人们能够对有关构念的结论有足够的信心。本文的目的是：（a）审视JAP当前的量表开发和评估实践；（b）将这些实践与推荐实践、以往实践以及其他期刊的实践进行比较；（c）利用这些比较结果，就测量方法的创建和评估向审稿人、编辑和研究者提出建议，包括针对各种指标的基于Excel的计算器。最后，鉴于模型复杂性似乎增加了对短量表的需求，我们提供了一个用户友好的R Shiny应用程序（https://orgscience.uncc.edu/about-us/resources），该程序可识别能使各种心理测量标准最大化的项目子集，而不仅仅是使阿尔法系数最大化。（《心理学文摘数据库记录》（c）2020美国心理学会，保留所有权利）
