Sib-pair genetic longitudinal studies with missing not at random data  

含非随机缺失数据的同胞对纵向研究

作　　者：Siyu Jiang and Hong Zhang 蒋思宇;张洪(中国科学技术大学管理学院统计与金融系,安徽合肥230026)

机构地区：[1]Department of Statistics and Finance,School of Management,University of Science and Technology of China,Hefei 230026,China

出　　处：《中国科学技术大学学报》2024年第12期16-21,I0003,I0008,共8页JUSTC

基　　金：This work was supported by the National Natural Science Foundation of China(12171451).

摘　　要：In the interdisciplinary realm of statistics,genetics,and epidemiology,longitudinal sibling pair data offers a unique perspective for investigating complex diseases and traits,allowing the exploration of the dynamic processes of gene expression over time by controlling numerous confounding factors.Missing-not-at-random(MNAR)data are commonly used in such types of studies,but no statistical methods specifically tailored have been developed to handle MNAR data in complex longitudinal data in the literature.Here,we propose a new statistical method by jointly modeling longitudinal data from sib-pairs and MNAR data.Extensive simulations demonstrate the excellent finite sample properties of the proposed method.在统计学、遗传学和流行病学的交叉领域中,纵向同胞对数据为研究复杂疾病和性状提供了独特的视角,可以揭示基因随时间变化的动态过程,同时控制众多混杂因素。在这类研究中常见到的是非随机缺失(MNAR)数据,但在过往研究中尚未开发专门用于处理复杂纵向数据中的MNAR数据的统计方法。本文提出了一个新的联合模型以刻画同胞对的纵向数据与非随机化缺失机制,基于该模型发展了新的统计推断方法。通过大量随机模拟展示了新方法的优良有限样本性质。

关 键 词：complex diseases gene-time interaction longitudinal data missing-not-at-random data 

分 类 号：O212.1[理学—概率论与数理统计]