Autoregressive modelling for the analysis of longitudinal data with unequally spaced examinations.
Autoregressive modelling for the analysis of longitudinal data with unequally spaced examinations.
复制标题
DOI：
10.1002/sim.4780070110
复制
发表时间：
1988
影响因子：
2
通讯作者：
B. Rosner;A. Muñoz
中科院分区：
文献类型：
--
作者：
B. Rosner;A. Muñoz
纵向研究中经常出现缺失和/或间隔不等的检查。提出了一个自回归模型来分析连续结果变量的此类数据。模型的拟合可以通过标准统计包中可用的加权非线性回归方法来完成。该模型的一些特征包括考虑时间依赖性和固定协变量、评估短期内结果变化和暴露之间的关系，以及使用个人的所有可用人员时间。其中包括一个插图，探讨个人吸烟对儿童肺功能变化的影响。
Missing and/or unequally spaced examinations are often present in longitudinal studies. An autoregressive model is presented for the analysis of such data for continuous outcome variables. The fitting of the model can be accomplished by weighted non-linear regression methods available in standard statistical packages. Some features of the model include consideration of both time-dependent and fixed covariates, assessment of the relationships between changes in outcome and exposure over short periods of time, and use of all available person-time for an individual. An illustration looking at the role of personal cigarette smoking on changes in pulmonary function in children is included.