Joint Modeling of Multivariate Longitudinal Data and Its Application

VernacularTitle:多个响应变量的纵向数据联合建模方法及应用
Author: Cunjie LIN ¹ ; Meng WU ; Danhui YI ; Jingqing HU
Author Information

1. 中国人民大学应用统计科学研究中心
Keywords: Multiple longitudinal data; linear mixed-effects model; joint modeling; random effects
From: World Science and Technology-Modernization of Traditional Chinese Medicine 2017;19(9):1443-1448
CountryChina
Language:Chinese
Abstract: Multiple outcomes measured repeatedly for the same subject are common in longitudinal observation.If we use the approach by analyzing each outcome separately,it may lead to wrong conclusions due to the failure of accounting for joint evolution of different outcomes.To adequately capture the interdependence among multiple outcomes,we proposed a joint modeling for multivariate longitudinal data by constructing a linear mixed-effects model for each outcome and accommodating the relationship among multiple outcomes through correlation in random effects.Maximum likelihood method was adopted to estimate parameters in this model.The application of this method was demonstrated through the analysis of stroke data.