王小磊,田梦圆,张娜,高红,谭红专.纵向数据中评估暴露总效应的序列条件平均模型[J].Chinese journal of Epidemiology,2020,41(1):111-114 |
纵向数据中评估暴露总效应的序列条件平均模型 |
A sequential conditional mean model for assessing total effects of exposure in longitudinal data |
Received:June 19, 2019 |
DOI:10.3760/cma.j.issn.0254-6450.2020.01.020 |
KeyWord: 序列条件平均模型 时依性协变量 倾向评分 广义估计方程 |
English Key Word: Sequential conditional mean model Time-dependent covariate Propensity score Generalized estimating equation |
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Author Name | Affiliation | E-mail | Wang Xiaolei | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China | | Tian Mengyuan | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China | | Zhang Na | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China Hunan Provincial People's Hospital/the First Affiliated Hospital of Hunan Normal University, Changsha 410016, China | | Gao Hong | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China | | Tan Hongzhuan | Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China | tanhz99@qq.com |
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Abstract: |
在前瞻性队列研究中,经常需要对研究对象进行多次随访,其产生的多个观测值之间相互关联,常导致时依性混杂,这种情况下的数据一般不满足传统的多因素回归分析的应用条件。序列条件平均模型(SCMM)是一种可以处理时依性混杂的新方法。本文主要对SCMM的基本原理、步骤及特点进行概括。 |
English Abstract: |
In prospective cohort study, multi follow up is often necessary for study subjects, and the observed values are correlated with each other, usually resulting in time-dependent confounding. In this case, the data generally do not meet the application conditions of traditional multivariate regression analysis. Sequential conditional mean model (SCMM) is a new approach that can deal with time-dependent confounding. This paper mainly summarizes the basic theory, steps and characteristics of SCMM. |
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