Schneiderman E D, Willis S M, Kowalski C J, Guo I Y
Department of Oral and Maxillofacial Surgery and Pharmacology, Baylor College of Dentistry, Dallas, TX 75266-0677.
Int J Biomed Comput. 1994 Jul;36(3):187-92. doi: 10.1016/0020-7101(94)90053-1.
Two stand-alone, menu-driven PC programs, written in GAUSS386i, which compare groups of growth curves in a completely randomized design using either (a) exact or (b) approximate randomization tests, are described, illustrated, and made available to interested readers. The programs accommodate missing data in the context of studies planned to have common times of measurement, but where some of the measurement sequences are incomplete. The measurement whose growth is being monitored need not have a Gaussian distribution. We consider the hypothesis that the mean growth curves in G groups are the same; and either compute the exact P value (exact test), or estimate, and provide a confidence interval for, the P value (approximate test).
介绍、举例说明了两个独立的、菜单驱动的用GAUSS386i编写的个人计算机程序，这些程序在完全随机设计中使用（a）精确或（b）近似随机化检验来比较多组生长曲线，并向感兴趣的读者提供。这些程序适用于在计划有共同测量时间但某些测量序列不完整的研究中处理缺失数据。被监测生长情况的测量值不必呈高斯分布。我们考虑G组中平均生长曲线相同的假设；然后计算精确P值（精确检验），或估计并提供P值的置信区间（近似检验）。
