摘要翻译：
纵向研究可能因左截尾重复测量而变得复杂。例如，在人类免疫缺陷病毒感染中，有一个检测限用于定量血浆病毒载量。对左截尾测度、偏差估计及其标准误差的检测极限或该极限的一半的简单估算。本文综述了两种基于似然的线性混合模型左截尾处理方法。我们展示了如何使用SAS Proc NLMIXID拟合这些模型，并将此工具与其他程序进行了比较。讨论了这些方案的适应症和局限性，并给出了HIV感染领域的一个例子。
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英文标题：
《Mixed models for longitudinal left-censored repeated measures》
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作者：
Rodolphe Thi\'ebaut, H\'el\`ene Jacqmin-Gadda
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最新提交年份：
2007
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分类信息：

一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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英文摘要：
  Longitudinal studies could be complicated by left-censored repeated measures. For example, in Human Immunodeficiency Virus infection, there is a detection limit of the assay used to quantify the plasma viral load. Simple imputation of the limit of the detection or of half of this limit for left-censored measures biases estimations and their standard errors. In this paper, we review two likelihood-based methods proposed to handle left-censoring of the outcome in linear mixed model. We show how to fit these models using SAS Proc NLMIXED and we compare this tool with other programs. Indications and limitations of the programs are discussed and an example in the field of HIV infection is shown.
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PDF链接：
https://arxiv.org/pdf/705.0569