相互依存
经验抽样法
采样(信号处理)
面子(社会学概念)
计算机科学
管理科学
领域(数学分析)
数据科学
现象
心理学
社会学
工程伦理学
认识论
社会心理学
社会科学
工程类
数学分析
哲学
滤波器(信号处理)
经济
数学
计算机视觉
作者
Allison S. Gabriel,Nathan P. Podsakoff,Daniel J. Beal,Brent A. Scott,Sabine Sonnentag,John P. Trougakos,Marcus M. Butts
标识
DOI:10.1177/1094428118802626
摘要
In the organizational sciences, scholars are increasingly using experience sampling methods (ESM) to answer questions tied to intraindividual, dynamic phenomenon. However, employing this method to answer organizational research questions comes with a number of complex—and often difficult—decisions surrounding: (1) how the implementation of ESM can advance or elucidate prior between-person theorizing at the within-person level of analysis, (2) how scholars should effectively and efficiently assess within-person constructs, and (3) analytic concerns regarding the proper modeling of interdependent assessments and trends while controlling for potentially confounding factors. The current paper addresses these challenges via a panel of seven researchers who are familiar not only with implementing this methodology but also related theoretical and analytic challenges in this domain. The current paper provides timely, actionable insights aimed toward addressing several complex issues that scholars often face when implementing ESM in their research.
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