Abstract
In medicine, there are often experiments characterized by repeated measurements on the same object. A well-known application are dose-finding studies where we try to prove a treatment effect in different doses. Establishing clinical trials in cross-over design, we have to prove both a dose and a group effect of the treatments as well as possible interactions between them. In principal, multivariate repeated measures analysis of variance (RM-ANOVA) can be used for the analysis of such a data structure (N.H. Timm (1980)). Difficulties arise if there are only a few observations available. In this case a parametric analysis of variance can not be applied anymore and we have to look for alternatives. In a first attempt and for reasons of easy practicability we applied the method of data alignment (Hildebrand (1980)) which consists of an adjustment of those factors not regarded in the current analysis and a following ranked analysis of variance.
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© 1999 Springer-Verlag Berlin · Heidelberg
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Wernecke, KD., Kalb, G. (1999). On Nonparametric Repeated Measures Analysis of Variance. In: Gaul, W., Locarek-Junge, H. (eds) Classification in the Information Age. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60187-3_65
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DOI: https://doi.org/10.1007/978-3-642-60187-3_65
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