Schneider B
Neuropsychobiology. 1983;10(1):49-55. doi: 10.1159/000117984.
In crossover or changeover designs, the different treatments are allocated to each experimental unit (e.g. patient in clinical trial) in a randomized order. To analyze the results of such experiments, a mixed analysis of variance model is usually assumed. But such a model implies unrealistic and unnecessary restrictions on the variance-co-variance structure. These restrictions can be avoided by assuming the measurements obtained from a unit (patient) as repeated measurements from a multivariate distributed random vector. The experimental effects are primarily characterized by the mean of this vector. The usually defined treatment, period and interaction (residual) effects are estimable functions of these mean values. In this paper, the general approach is discussed and parametric as well as nonparametric tests for the various hypotheses are presented. This approach is developed in detail for the two-period crossover design and demonstrated with an example.
在交叉或转换设计中，不同的治疗方法以随机顺序分配给每个实验单位（如临床试验中的患者）。为了分析此类实验的结果，通常假定采用混合方差分析模型。但这样的模型对方差协方差结构隐含了不现实且不必要的限制。通过将从一个单位（患者）获得的测量值假定为来自多元分布随机向量的重复测量值，可以避免这些限制。实验效应主要由该向量的均值来表征。通常定义的治疗、时期和交互（残差）效应是这些均值的可估计函数。本文讨论了一般方法，并给出了针对各种假设的参数检验和非参数检验。针对两期交叉设计详细阐述了该方法，并通过一个例子进行了说明。
