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流行队列研究与未观察到的异质性。

Prevalent cohort studies and unobserved heterogeneity.

作者信息

Keiding Niels, Albertsen Katrine Lykke, Rytgaard Helene Charlotte, Sørensen Anne Lyngholm

机构信息

Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark.

出版信息

Lifetime Data Anal. 2019 Oct;25(4):712-738. doi: 10.1007/s10985-019-09479-9. Epub 2019 Jul 3.

Abstract

Consider lifetimes originating at a series of calendar times [Formula: see text]. At a certain time [Formula: see text] a cross-sectional sample is taken, generating a sample of current durations (backward recurrence times) of survivors until [Formula: see text] and a prevalent cohort study consisting of survival times left-truncated at the current durations. A Lexis diagram is helpful in visualizing this situation. Survival analysis based on current durations and prevalent cohort studies is now well-established as long as all covariates are observed. The general problems with unobserved covariates have been well understood for ordinary prospective follow-up studies, with the good help of hazard rate models incorporating frailties: as for ordinary regression models, the added noise generates attenuation in the regression parameter estimates. For prevalent cohort studies this attenuation remains, but in addition one needs to take account of the differential selection of the survivors from initiation [Formula: see text] to cross-sectional sampling at [Formula: see text]. This paper intends to survey the recent development of these matters and the consequences for routine use of hazard rate models or accelerated failure time models in the many cases where unobserved heterogeneity may be an issue. The study was inspired by concrete problems in the study of time-to-pregnancy, and we present various simulation results inspired by this particular application.

摘要

考虑从一系列日历时间[公式:见正文]开始的生存时间。在某个时间[公式:见正文]进行横断面抽样,生成直到[公式:见正文]的幸存者当前持续时间(反向复发时间)的样本,以及由在当前持续时间处左截断的生存时间组成的现患队列研究。Lexis图有助于直观呈现这种情况。只要观察到所有协变量,基于当前持续时间和现患队列研究的生存分析现已确立。对于普通前瞻性随访研究,在纳入脆弱性的风险率模型的良好帮助下,未观察到的协变量的一般问题已得到很好理解:与普通回归模型一样,额外的噪声会导致回归参数估计值的衰减。对于现患队列研究,这种衰减仍然存在,但此外还需要考虑从起始[公式:见正文]到在[公式:见正文]进行横断面抽样时幸存者的差异选择。本文旨在综述这些问题的最新进展,以及在未观察到的异质性可能成为问题的许多情况下,对风险率模型或加速失效时间模型常规使用的影响。该研究受到妊娠时间研究中的具体问题的启发,并且我们展示了受此特定应用启发的各种模拟结果。

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