Chou Chih-Ping, Chi Felicia, Weisner Constance, Pentz Maryann, Hser Yih-Ing
J Drug Issues. 2010 Dec;40(1):155-172. doi: 10.1177/002204261004000109.
The growth curve modeling (GCM) technique has been widely adopted in longitudinal studies to investigate progression over time. The simplest growth profile involves two growth factors, initial status (intercept) and growth trajectory (slope). Conventionally, all repeated measures of outcome are included as components of the growth profile, and the first measure is used to reflect the initial status. Selection of the initial status, however, can greatly influence study findings, especially for randomized trials. In this article, we propose an alternative GCM approach involving only post-intervention measures in the growth profile and treating the first wave after intervention as the initial status. We discuss and empirically illustrate how choices of initial status may influence study conclusions in addressing research questions in randomized trials using two longitudinal studies. Data from two randomized trials are used to illustrate that the alternative GCM approach proposed in this article offers better model fitting and more meaningful results.
生长曲线建模（GCM）技术已在纵向研究中被广泛采用，以调查随时间的进展情况。最简单的生长概况涉及两个生长因素，即初始状态（截距）和生长轨迹（斜率）。按照惯例，所有重复的结局测量值都被纳入生长概况的组成部分，且首次测量值用于反映初始状态。然而，初始状态的选择会极大地影响研究结果，尤其是对于随机试验而言。在本文中，我们提出了一种替代性的GCM方法，该方法在生长概况中仅涉及干预后的测量值，并将干预后的第一波测量视为初始状态。我们通过两项纵向研究，讨论并实证说明了初始状态的选择在解决随机试验中的研究问题时可能如何影响研究结论。来自两项随机试验的数据用于说明本文提出的替代性GCM方法能提供更好的模型拟合和更有意义的结果。
