放弃分析:一种基于互联网的研究和dropR数据的方法,一个基于R的Web应用程序和包,用于分析和可视化放弃数据
Ulf-Dietrich Reips1, Annika T Overlander2, Matthias Bannert3
1Department of Psychology, University of Konstanz, Universitätsstr. 10, 78464, Konstanz, Germany. reips@uni-konstanz.de.
Behavior research methods
|July 18, 2025
概括
本研究介绍了dropR,这是一个免费的R包和Web应用程序,旨在分析和可视化基于互联网的研究中的参与者学. dropR为研究人员简化了复杂的退学数据分析,提供准备发布的可视化和统计洞察力.
科学领域:
- 心理学 心理学 心理学
- 计算机科学 计算机科学
- 统计 统计 统计 统计
背景情况:
- 基于互联网的研究带来了与参与者不响应的独特挑战,包括项目不响应和学.
- 在线研究的自愿性和大样本大小需要强大的方法来分析学.
- 退学分析对于理解数字环境中的数据完整性和研究有效性至关重要.
研究的目的:
- 开发和讨论分析基于互联网的研究中学的方法.
- 介绍dropR,一个R包和用于分析和可视化dropout数据的Web服务.
- 为研究人员提供可访问的工具,以了解和呈现参与者退缩.
主要方法:
- 开发了dropRR包和Shiny网络应用程序.
- 使用R进行统计计算和放弃曲线的图形表示.
- 实施统计测试,包括千平方,赔率比,卡普兰-梅尔生存分析,科尔莫戈罗夫-斯米尔诺夫和罗家族统计.
主要成果:
- dropR生成可访问的,准备发布的退出曲线可视化.
- 该套件计算了关键的失业参数,如千平方值和赔率比率.
- 自动推理组件识别临界脱落点和实验条件之间的差异.
结论:
- dropR提供了一种用户友好的解决方案,用于分析和可视化基于互联网的研究中,不需要编程知识.
- 该工具通过提供统计见解和视觉显示来增强数据解释.
- 作为一个免费的Web应用程序和R包,dropR支持研究人员解决参与者退出问题.
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