A Likelihood Based Approach for Joint Modeling of Longitudinal Trajectories and Informative Censoring Process.
A Likelihood Based Approach for Joint Modeling of Longitudinal Trajectories and Informative Censoring Process.
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基于似然的纵向轨迹和信息审查过程联合建模方法。
DOI：
10.1080/03610926.2018.1473599
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Jaffa,AyadA
中科院分区：
文献类型：
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作者：
Jaffa,MiranA;Jaffa,AyadA
我们提出了一个联合建模似然为基础的方法，重复测量和信息权删失的研究。纵向和生存数据的联合建模是常用方法，但如果违反风险比例，可能导致偏倚估计。为了克服这个问题，并且考虑到脱落的确切时间通常是未知的，我们将删失时间建模为随访访视的次数，并将其扩展为取决于选定的协变量。对每例受试者的纵向轨迹进行建模，以了解疾病进展，并将其与一个似然函数中的随访访视次数合并。
We propose a joint modeling likelihood-based approach for studies with repeated measures and informative right censoring. Joint modeling of longitudinal and survival data are common approaches but could result in biased estimates if proportionality of hazards is violated. To overcome this issue, and given that the exact time of dropout is typically unknown, we modeled the censoring time as the number of follow-up visits and extended it to be dependent on selected covariates. Longitudinal trajectories for each subject were modeled to provide insight into disease progression and incorporated with the number follow-up visits in one likelihood function.