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BRUNNER, E., DOMHOF, S. and LANGER, F. Nonparametric Analysis of Longitudinal Data in Factorial Experiments. Wiley, New York, 2002. xvii + 261 pp. L70.50/ $94.95. ISBN 0-471-44166-X.
Longitudinal data consist of observations obtained at different time points from each experimental unit. Typical techniques for analysing longitudinal data are based on general linear models, generalized linear models and growth curve models. Computer programs like SAS Proc Mixed can be used to analyse longitudinal data parametrically.
In this book the author present nonparametric techniques for analysing longitudinal data obtained from factorial experiments, based on research mainly done by the authors and their colleagues during the last twenty years. In particular, the authors try to provide 'a unified approach for the analysis of factorial designs involving longitudinal data that is appropriate for metric data, count data, ordered categorical data, and dichotomous data.'
Following the recent trend, the authors present 14 studies in...