稳健性
心理信息
心理学
多样性(控制论)
心理测量学
比例(比率)
梅德林
应用心理学
社会心理学
临床心理学
计算机科学
法学
政治学
程序设计语言
人工智能
物理
量子力学
作者
José M. Cortina,Zitong Sheng,Sheila K. Keener,Kathleen R. Keeler,Leah Katell Grubb,Neal Schmitt,Scott Tonidandel,Karoline Summerville,Eric D. Heggestad,George C. Banks
摘要
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).
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