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分位数回归模型在公共卫生领域中的应用及SAS实现

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目的 探讨分位数回归模型在公共卫生领域中应用及 SAS实现,为该方法推广使用提供参考.方法 在介绍分位数回归模型基本概念基础上,介绍了分位数回归模型应用情景与优势,并以血清克拉拉细胞蛋白水平和第一秒用力呼气容积/用力肺活量(FEV1/FVC)变化数据为例,与简单线性回归模型相比,探讨分位数回归模型应用及 SAS实现过程.结果 分位数回归模型不仅可以分析血清克拉拉细胞蛋白水平对 FEV1/FVC 均值的影响,还可以分析血清克拉拉细胞蛋白水平对FEV1/FVC不同分位数的影响,得到更全面的信息,且通过统计软件 SAS可方便实现.结论 分位数回归模型可弥补简单线性回归模型仅关注应变量均值特征而不能分析其完整分布特征的不足,SAS软件提供了相对成熟的分析语句,值得推广.
Application of quantile regression model in public health and realization of SAS
Objective To explore the application of quantile regression models in public health and its SAS implementation,so as to provide a reference for the promotion of this method.Methods Based on the introduction of the basic concept of quantile regression model,the application situation and advantages of quantile regression model are introduced.The application of quantile regression mod-el and its SAS implementation are discussed by performing simple linear regression model as a contrast when data of serum Clara cell protein levels and FEV1/FVC changes were used as an example.Results Compared with the simple linear regression model,the quantile regression model could not only analyze the impact of serum Clara cell protein levels on the mean FEV1/FVC,but also analyze the effects of serum Clara cell protein levels on different quantiles of FEV1/FVC to obtain more comprehensive information,which could be easily achieved by statistical software SAS.Conclusion Quantile regression models can compensate for the deficiency of simple lin-ear regression models that only focuses on the mean value of the dependent variables but not complete distribution characteristics,and software SAS provides relatively mature analytic expressions,which is worth promotion.

quantile regressiondistribution characteristicspublic healthsoftware SAS

张紫琦、王爱玲、屈水令、王潇滟、于石成、潘晓平

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中国疾病预防控制中心妇幼保健中心,北京 100081

中国疾病预防控制中心

分位数回归 分布特征 公共卫生 SAS

2024

环境卫生学杂志
中国疾病预防控制中心

环境卫生学杂志

CSTPCD
影响因子:0.735
ISSN:2095-1906
年,卷(期):2024.14(1)
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