Zheng Cheng, Tong Lili, Zhang Ying
Department of Biostatistics, University of Nebraska Medical Center, Omaha, Nebraska, 68198, USA.
J R Stat Soc Ser C Appl Stat. 2024 Jan;73(1):104-122. doi: 10.1093/jrsssc/qlad087. Epub 2023 Sep 13.
Cognitive impairment has been widely accepted as a disease progression measure prior to the onset of Huntington's disease. We propose a sophisticated measurement error correction method that can handle potentially correlated measurement errors in longitudinally collected exposures and multiple outcomes. The asymptotic theory for the proposed method is developed. A simulation study is conducted to demonstrate the satisfactory performance of the proposed two-stage fitting method and shows that the independent working correlation structure outperforms other alternatives. We conduct a comprehensive longitudinal analysis to assess how brain striatal atrophy affects impairment in various cognitive domains for Huntington's disease.
认知障碍已被广泛接受为亨廷顿舞蹈病发病前疾病进展的一种衡量指标。我们提出了一种复杂的测量误差校正方法,该方法可以处理纵向收集的暴露因素和多个结局中潜在的相关测量误差。并为所提出的方法建立了渐近理论。进行了一项模拟研究,以证明所提出的两阶段拟合方法具有令人满意的性能,并表明独立工作相关结构优于其他方法。我们进行了一项全面的纵向分析,以评估脑纹状体萎缩如何影响亨廷顿舞蹈病患者在各个认知领域的功能损害。