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临床流行病学研究中多因素分析时的变量选择方法

Variable selection methods for multivariable analysis in clinical epidemiological studies
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摘要 变量选择是多因素分析时必不可少的环节,在控制混杂因素或者使模型达到高预测性能方面起着至关重要的作用。目前常用的变量筛选方法主要分为数据驱动和知识驱动两大类别,不同的变量筛选方法在识别混杂因素的作用、适用条件方面各不相同。本文介绍了临床流行病学中常用的变量筛选方法,并分析了这些方法优势和局限性,尤其是详细介绍了基于“知识驱动”的变量筛选方法在因果推断的临床研究中识别混杂变量的重要性,是当前国际上提高多因素分析结果的准确性和因果推断有效性的重要手段之一。本文也指出了国内研究者采用的变量筛选方法和国际上高质量研究的差别,并对不同临床研究情况下的变量筛选方法提出了合理的建议,旨在帮助临床研究者更好地了解和选择合适的变量筛选方法,提高临床研究的质量。
作者 聂朦 邬娜 袁志权 夏婷婷 向颖 李亚斐 Nie Meng;Wu Na;Yuan Zhiquan;Xia Tingting;Xiang Ying;Li Yafei(Clinical Epidemiology and Evidence Based Medicine Center,Department of Epidemiology,Faculty of Military Preventive Medicine,Army Medical University(Third Military Medical University),Chongqing 400038,China;School of Public Health,the Key Laboratory of Environmental Pollution Monitoring and Disease Control,Ministry of Education,Guizhou Medical University,Guiyang 561113,China)
出处 《中华内科杂志》 CAS CSCD 北大核心 2024年第5期462-467,共6页 Chinese Journal of Internal Medicine
基金 国家自然科学基金(82073649)。
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