Abdolell M, LeBlanc M, Stephens D, Harrison R V
Population Health Sciences Research Institute, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada.
Stat Med. 2002 Nov 30;21(22):3395-409. doi: 10.1002/sim.1266.
We investigate a binary partitioning algorithm in the case of a continuous repeated measures outcome. The procedure is based on the use of the likelihood ratio statistic to evaluate the performance of individual splits. The procedure partitions a set of longitudinal data into two mutually exclusive groups based on an optimal split of a continuous prognostic variable. A permutation test is used to assess the level of significance associated with the optimal split, and a bootstrap confidence interval is obtained for the optimal split.
我们研究了在连续重复测量结果情况下的一种二元分割算法。该程序基于使用似然比统计量来评估各个分割的性能。该程序根据连续预后变量的最优分割将一组纵向数据划分为两个相互排斥的组。使用置换检验来评估与最优分割相关的显著性水平，并获得最优分割的自助置信区间。
