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在瑞典问卷中关于职业的开放式答案中为办公室工作者分配一个代理变量的数据
Annika Tillander1, Susanna Lehtinen-Jacks2, Nisha Singh2
1Department of Computer and Information Science (IDA), Division of Statistics and Machine Learning (STIMA), Linköping University, 581 83 Linköping, Sweden.
Data in brief
|October 20, 2025
概括
研究人员开发了R代码来识别办公室工作者从瑞典研究中自我报告的职位头. 这种方法通过使用职业数据,增强了对工人健康和福利的流行病学研究.
科学领域:
- 流行病学 流行病学
- 职业健康 职业健康 职业健康
- 社会科学 社会科学 社会科学
背景情况:
- 比较职业群体,如办公室与非办公室工作者,在流行病学中至关重要.
- 自我报告的职业头通常是分类的唯一可用的数据.
- 识别办公室工作人员对于研究他们的健康结果至关重要.
研究的目的:
- 引入R代码和一个代理变量,用于从开放式职业问题中识别办公室工作人员.
- 促进对办公室工作者的健康进行大规模的流行病学研究.
- 为了使个人可以被归类为白领或蓝领工人.
主要方法:
- 使用了2012年瑞典职业标准分类 (SSYK 2012).
- 开发了一个翻译密钥,将8946个职业名称分类为经理,白领和蓝领工人.
- 通过使用LifeGene资源的试点数据来改进代理变量.
主要成果:
- 创建了一个代理变量来将白领工人 (包括经理) 分类为办公室工人.
- 蓝领工人被归类为非办公室工人.
- R代码成功地根据职业头对受访者进行了分类.
结论:
- R 代码和代理变量使办公室工作者从开放式职业问题中进行识别.
- 该方法适用于任何具有瑞典职业OEQ的数据集,并且可以适用于其他语言.
- 增强基于人口的流行病学研究的研究能力.
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