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Correlated multistate models for multiple processes: an application to renal disease progression in systemic lupus erythematosus.
The Journal of the Royal Statistical Society: Series C (Applied Statistics) ( IF 1.6 ) Pub Date : 2019-05-21 , DOI: 10.1111/rssc.12257
Aidan G O'Keeffe 1 , Li Su 2 , Vernon T Farewell 2
Affiliation  

Bidirectional changes over time in the estimated glomerular filtration rate and in urine protein content are of interest for the treatment and management of patients with lupus nephritis. Although these processes may be modelled by separate multistate models, the processes are likely to be correlated within patients. Motivated by the lupus nephritis application, we develop a new multistate modelling framework where subject-specific random effects are introduced to account for the correlations both between the processes and within patients over time. Models are fitted by using bespoke code in standard statistical software. A variety of forms for the random effects are introduced and evaluated by using the data from the Systemic Lupus International Collaborating Clinics.

中文翻译:

用于多个过程的相关多状态模型:在系统性红斑狼疮肾脏疾病进展中的应用。

估计的肾小球滤过率和尿液蛋白含量随时间的双向变化对于狼疮性肾炎患者的治疗和治疗很重要。尽管可以通过单独的多状态模型对这些过程进行建模,但是这些过程很可能在患者中相关。受狼疮性肾炎应用的启发,我们开发了一种新的多状态建模框架,其中引入了受治疗者特定的随机效应,以说明过程之间以及患者内部随时间的相关性。通过使用标准统计软件中的定制代码来拟合模型。通过使用系统性红斑狼疮国际合作诊所的数据,介绍并评估了各种形式的随机效应。
更新日期:2019-11-01
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