Fitzmaurice G M, Laird N M
Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
Biostatistics. 2000 Jun;1(2):141-56. doi: 10.1093/biostatistics/1.2.141.
This paper presents a method for analysing longitudinal data when there are dropouts. In particular, we develop a simple method based on generalized linear mixture models for handling nonignorable dropouts for a variety of discrete and continuous outcomes. Statistical inference for the model parameters is based on a generalized estimating equations (GEE) approach (Liang and Zeger, 1986). The proposed method yields estimates of the model parameters that are valid when nonresponse is nonignorable under a variety of assumptions concerning the dropout process. Furthermore, the proposed method can be implemented using widely available statistical software. Finally, an example using data from a clinical trial of contracepting women is used to illustrate the methodology.
本文提出了一种在存在失访情况下分析纵向数据的方法。具体而言，我们基于广义线性混合模型开发了一种简单方法，用于处理各种离散和连续结局的不可忽略失访情况。模型参数的统计推断基于广义估计方程（GEE）方法（Liang和Zeger，1986年）。在关于失访过程的各种假设下，当无应答不可忽略时，所提出的方法会产生有效的模型参数估计值。此外，所提出的方法可以使用广泛可用的统计软件来实现。最后，使用来自一项避孕妇女临床试验的数据示例来说明该方法。
