首页|含有测量误差与缺失值的纵向数据亚组分析方法的模拟研究

含有测量误差与缺失值的纵向数据亚组分析方法的模拟研究

Simulation of Subgroup Analysis Methods with Longitudinal Data Containing Measurement Errors and Missingness

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目的 研究可以同时处理协变量含有测量误差和响应变量含有缺失值的纵向数据下的亚组分析方法.方法 基于阈值回归模型进行亚组分析;利用重复测量之间的独立性来处理测量误差,并引入逆概率加权来处理缺失值,从而构造一个新的广义渐近无偏估计方程.结果 计算机随机模拟显示该估计方法在处理测量误差和缺失数据方面具有良好的效果,相比于未修正测量误差或缺失数据的广义估计方程方法具有更小的偏倚和均方误差.结论 亚组分析中,当协变量存在测量误差、响应变量存在缺失值时,通常需要考虑对测量误差和缺失值进行处理,以便得到可靠的参数估计.
Objective To develop a subgroup analysis method that can simultaneously deal with longitudinal data containing measurement errors and dropouts.Methods Subgroup analysis was carried out based on a threshold regression model.A new generalized unbiased estimation equation is constructed by using the independence between repeated measurements to deal with measurement errors and introducing an inverse probability weighting matrix to deal with missing response.Results The computer stochastic simulation shows that the proposed estimation method is effective in dealing with measurement errors and dropouts,and has smaller bias and mean square error than the generalized estimation equation method without correcting measurement errors or dropouts.Conclusion In subgroup analysis,when there are measurement errors in covariables and missing values in response variables,it is usually necessary to deal with the measurement errors and missing values in order to obtain reliable parameter estimation.

Subgroup analysisLongitudinal dataGeneralized estimation equationMeasurement errorMissing value

薛雅心、秦国友

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复旦大学公共卫生学院生物统计学教研室(200032)

亚组分析 纵向数据 广义估计方程 测量误差 缺失值

国家自然科学基金

11871164

2024

中国卫生统计
中国卫生信息学会 中国医科大学

中国卫生统计

CSTPCD北大核心
影响因子:1.172
ISSN:1002-3674
年,卷(期):2024.41(1)
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