测量方法的比较,以评估二的形状相似性
Chiara Carlier1, Julian D Karch2, Peter Kuppens1
1Department of Psychology and Educational Sciences, KU Leuven, Belgium.
Psychologica Belgica
|July 1, 2024
概括
这项研究通过比较43种情感数据方法来澄清个人资料相似度. 建议包括避免皮尔森相关性和集中项目以改善相似性计算.
科学领域:
- 心理测量 心理测量 心理测量
- 数据分析 数据分析
背景情况:
- 配置文件相似度的测量对于在变量之间比较评级集至关重要.
- 不同的措施所传达的区别,重叠和信息存在缺乏清晰度.
- 这种模两可,阻碍了对各种研究环境的适当措施的选择.
研究的目的:
- 阐明现有的个人资料相似度指标之间的相互关系.
- 为选择和应用这些措施提供基于证据的建议.
- 提高研究中相似性分析的理解和应用.
主要方法:
- 对88个相似度进行了全面审查.
- 测量适用于横截面和强度纵向情感体验数据集.
- 经过严格的过后,保留了43个措施,随后进行了聚类和理论解释.
主要成果:
- 确定了三个主要的相似度指标集群:差异,产品和各种.
- 产品和各种集群进一步细化为细微的子组.
- 每个措施组传递的独特信息都基于理论框架和公式来解释.
结论:
- 该研究提供了对个人资料相似度指标及其行为的结构化理解.
- 为措施选择提供了建议,主张避免皮尔森相关性.
- 建议将个人资料项目放在中心,以减轻刻板印象模式的混效应.
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