Nested analysis of variance with autocorrelated errors

In this paper we consider the problem where there is a randomized experimental design with several successive time measurements on each experimental unit. One approach to the analysis of such data is to treat time as the subplot treatment and to use a split-plot analysis of variance. Alternatively, the problem may be considered in a more general multivariate framework. Here we recognize the time-induced correlations and apply an autoregressive time series modelling approach. Estimation and testing are addressed. Two examples are presented to illustrate the practicality of our procedure. Some extensions are also considered briefly.