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响应缺失与协变量测量误差下纵向研究的函数型广义矩方法AI 解读

Abstract Covariate measurement error and missing responses are typical features in longitudinal data analysis. There has been extensive research on either covariate measurement error or missing responses, but relatively little work has been done to address both simultaneously. In this paper, we propose a simple method for the marginal analysis of longitudinal data with time-varying covariates, some of which are measured with error, while the response is subject to…

响应与协变量随机缺失的纵向数据加权广义估计函数AI 解读

Longitudinal studies often feature incomplete response and covariate data. It is well known that biases can arise from naive analyses of available data, but the precise impact of incomplete data depends on the frequency of missing data and the strength of the association between the response variables and covariates and the missing-data indicators. Various factors may influence the availability of response and covariate data at scheduled assessment times, and at any given…