吴诗蓝,周价,李逊,黄麟婷,张佳月,郭楚豪,龙斯思,谭红专.Parametric g-formula方法在因果分析中的应用[J].Chinese journal of Epidemiology,2019,40(10):1310-1313 |
Parametric g-formula方法在因果分析中的应用 |
Application of parametric g-formula in causal analysis |
Received:January 27, 2019 |
DOI:10.3760/cma.j.issn.0254-6450.2019.10.025 |
KeyWord: 时依性混杂 Parametric g-formula方法 因果分析 |
English Key Word: Time-varying confounding Parametric g-formula method Causal analysis |
FundProject:国家自然科学基金(81773535) |
Author Name | Affiliation | E-mail | Wu Shilan | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008, China | | Zhou Jia | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008, China | | Li Xun | Institute of Pediatric Research, Hunan Children's Hospital, Changsha 410007, China | | Huang Linting | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008, China | | Zhang Jiayue | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008, China | | Guo Chuhao | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008, China | | Long Sisi | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008, China | | Tan Hongzhuan | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008, China | tanhz99@qq.com |
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Abstract: |
目前,传统的统计学方法在控制时依性混杂等方面存在局限,本研究详细介绍了一种可调整时依性混杂的分析方法——parametric g-formula,并举例说明了实施的具体步骤,为研究者处理长期观察性数据提供了新的参考。 |
English Abstract: |
At present, traditional methods on statistics have limitations in controlling time- varying confounding. This paper introduces an analysis method, parametric g-formula, which would adjust time-varying confounding, and also exemplifies the steps of its implementation for purpose to provide a new reference for researchers to deal with long-term observational data. |
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