经验采样方法的新发展
Francis Tuerlinckx1, Peter Kuppens1, Sigert Ariens1
1Faculty of Psychology and Educational Sciences, KU Leuven-University of Leuven, Leuven, Belgium.
概括
经验采样方法 (ESM) 推动了对日常生活感受和行为的研究. 本文回顾了最近在ESM设计,统计分析和实施方面取得的进展,以加强数据收集和解释.
科学领域:
- 心理学科学 心理学科学
- 行为科学 行为科学
- 方法论 方法论 方法论
背景情况:
- 经验采样方法 (ESM) 是研究现实生活经验的强大工具.
- 它的广泛采用需要方法更新.
- 最近的进展主要集中在改善ESM研究中的数据收集和分析.
研究的目的:
- 提供关于ESM最近的方法进步的全面概述.
- 讨论ESM设计,统计分析和实施方面的创新.
- 要突出这些进步在研究影响在日常生活中的应用.
主要方法:
- 审查关于ESM设计,统计分析和实施的最新文献.
- 讨论自我报告措施,移动传感,爆发设计和样本大小规划.
- 探索非线性模型,生存分析,实时监测,开放科学和数据预处理.
主要成果:
- 最近的ESM发展提高了收集数据的可靠性和有效性.
- 先进的统计技术为时间序列和时间到事件数据提供了更深入的见解.
- 改进的实施策略有助于开放的科学和高效的数据处理.
结论:
- 方法上的进步对于最大限度地发挥ESM的潜力至关重要.
- 这些创新支持对日常生活现象进行更强大,更深刻的研究.
- 讨论的方法是广泛适用的,重点是影响研究.
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