Hassani H, Ebbutt A
Glaxo Wellcome Research and Development, Middlesex, U.K.
Stat Med. 1996 Dec 15;15(23):2617-27. doi: 10.1002/(SICI)1097-0258(19961215)15:23<2617::AID-SIM376>3.0.CO;2-P.
We discuss a stochastic model appropriate for binary data in clinical studies where assessments are made at various nominal times during a treatment phase. The model is then applied to data on headache relief, nausea and photophobia/phonophobia in a migraine study. The transition rates and probabilities during the initial 240 minutes after treatment administration are derived using the method of maximum likelihood. The results are then compared with analysis at each nominal time point. Stochastic modelling is considered more appropriate for the analysis of repeated binary assessments than analysis at each nominal time since each patient's assessments are modelled simultaneously.
我们讨论一种适用于临床研究中二元数据的随机模型，在治疗阶段的不同标称时间进行评估。然后将该模型应用于偏头痛研究中关于头痛缓解、恶心和畏光/畏声的数据。使用最大似然法得出给药后最初240分钟内的转移率和概率。然后将结果与每个标称时间点的分析进行比较。与在每个标称时间进行分析相比，随机建模被认为更适合对重复二元评估进行分析，因为每个患者的评估是同时建模的。
