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APPLIED MULTIVARIATE STATISTICS: WITH SAS® SOFTWARE by Dayanand N. Naik, Ravindra Khattree

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5.7. Crossover Designs

In crossover experiments, treatments are administered in a variety of sequences on various subjects. Thus, each subject may get more than one treatment in the course of the experiment. One reason for doing so is that there is usually more variability across subjects than within subjects. Hence the subjects can be treated as random blocks for the purpose of increasing the precision by controlling experimental error variance. The problem, however, becomes complicated by the fact that the successive measurements on the subjects may be correlated. There is also the possible presence of carryover effect(s) at a given time point, from the treatment(s) applied at previous time point(s). This calls for a careful analysis of the ...

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