构造(python库)
操作化
概念化
结构效度
等价(形式语言)
心理学
检查表
理论定义
比例(比率)
实证研究
计算机科学
管理科学
心理测量学
认知心理学
数学
认识论
人工智能
发展心理学
哲学
物理
离散数学
量子力学
经济
程序设计语言
作者
Lisa Schurer Lambert,Daniel A. Newman
标识
DOI:10.1177/10944281221115374
摘要
We review contemporary best practice for developing and validating measures of constructs in the organizational sciences. The three basic steps in scale development are: (a) construct definition, (b) choosing operationalizations that match the construct definition, and (c) obtaining empirical evidence to confirm construct validity. While summarizing this 3-step process [i.e., Define-Operationalize-Confirm], we address many issues in establishing construct validity and provide a checklist for journal reviewers and authors when evaluating the validity of measures used in organizational research. Among other points, we pay special attention to construct conceptualization, acknowledging existing constructs, improving existing measures, multidimensional constructs, macro-level constructs, and the need for independent samples to confirm construct validity and measurement equivalence across subpopulations.
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