利用机器学习揭示年龄与生活满意度之间的关系。
Using machine learning to uncover the relation between age and life satisfaction.
机构信息
Department of Management, Society, and Communication, Copenhagen Business School, Dalgas Have 15, 2000, Frederiksberg, Denmark.
Institute for Health Care and Public Management, University of Hohenheim, Fruwirthstrasse 48, 70599, Stuttgart, Germany.
出版信息
Sci Rep. 2022 Mar 28;12(1):5263. doi: 10.1038/s41598-022-09018-x.
This study applies a machine learning (ML) approach to around 400,000 observations from the German Socio-Economic Panel to assess the relation between life satisfaction and age. We show that with our ML-based approach it is possible to isolate the effect of age on life satisfaction across the lifecycle without explicitly parameterizing the complex relationship between age and other covariates-this complex relation is taken into account by a feedforward neural network. Our results show a clear U-shape relation between age and life satisfaction across the lifespan, with a minimum at around 50 years of age.
本研究应用机器学习（ML）方法对来自德国社会经济面板的约 40 万条观测值进行分析，以评估生活满意度和年龄之间的关系。我们表明，通过我们基于 ML 的方法，有可能在不明确参数化年龄与其他协变量之间复杂关系的情况下，在整个生命周期内隔离年龄对生活满意度的影响——这种复杂关系由前馈神经网络考虑在内。我们的研究结果表明，在整个生命周期内，年龄与生活满意度之间存在明显的 U 型关系，在大约 50 岁时达到最小值。
Zotero 插件