开放集群 (OpenClustered):一个R包,包含一个基准集群数据集套件,用于方法评估和比较
Nathaniel Sean O'Connell1, Jaime Lynn Speiser2
1Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA.
BMC medical research methodology
|April 11, 2025
概括
一个新的R包,OpenClustered,提供19个开源集群数据集用于方法比较. 该资源提供经验指导,减少偏差与集群数据分析的传统数据模拟研究相比.
科学领域:
- 统计 统计 统计 统计
- 数据科学数据科学数据科学
- 生物信息学是一种生物信息学.
背景情况:
- 在流行病学和社会科学中常见的集群数据,在群体内表现出相关性.
- 现有的数据存储库缺乏对集群数据集的全面资源.
- 传统的模拟研究用于方法评估可以引入偏见.
研究的目的:
- 为集群数据集开发一个开源数据库.
- 为了促进方法论的比较和基准研究.
- 为可能存在偏见的数据模拟提供替代方案.
主要方法:
- 开发R包"开放集群"的开发.
- 包括19个不同的集群数据集与二进制结果.
- 创建用于数据处理和分析的教程.
主要成果:
- 开放集群软件包提供了19个不同大小和组成的集群数据集.
- 教程展示了数据集过,总结和基准测试.
- 一项试点研究使用该包比较了Frequentist和贝叶斯通用线性混合模型.
结论:
- 开源集群作为一个有价值的资源,用于对比研究与开源集群数据.
- 该方案促进经验方法指导,增强研究的严谨性.
- 未来的计划包括扩大数据集收集和用户提交功能.
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