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数学学院、所系列学术报告(705场):美国密苏里大学Hongyuan Cao教授

admin 发表于: 2017-06-13 15:19  点击:157

    题 目:On last observation carried forward and asynchronous longitudinal

regression analysis.

    报告人:美国密苏里大学Hongyuan Cao教授

    时  间:6月14日 上午9:00---11:00

    地  点:数学楼629

                                   

In many longitudinal studies, the covariates and response are often intermittently observed at irregular, mismatched and subject-specific times. Last observation carried forward (LOCF) is one of the most commonly used methods to deal with such data when covariates and response are observed asynchronously. However, this can lead to considerable bias. In this paper, we propose a weighted LOCF estimation using asynchronous longitudinal data for the generalized linear model. We further generalize this approach to utilize previously observed covariates in addition to the most recent observation. In comparison to earlier methods, the current methods are valid under weaker assumptions on the covariate process and allow informative observation times which may depend on response even conditional on covariates. Extensive simulation studies provide numerical support for the theoretical findings. Data from an HIV study is used to illustrate our methodology.