Abstract
Continuous data from crossover trials are often analysed using ordinary least squares with the assumption of independent errors. Because each experimental unit receives a sequence of treatment and repeated measurements are collected, it is more realistic to assume that the errors within an experimental unit are correlated. In this paper, we extend to crossover designs the conditions on the covariance structure of the errors, found by Huynh and Feldt (1970) for randomized block and split-plot designs, that will not invalidate the F-ratio tests for treatment and carryover effects. We also show that results on optimal crossover designs remain valid under this more general structure of the covariance matrix.
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Bellavance, F., Tardif, S. (2005). Conditions for the Validity of F-Ratio Tests for Treatment and Carryover Effects in Crossover Designs. In: Duchesne, P., RÉMillard, B. (eds) Statistical Modeling and Analysis for Complex Data Problems. Springer, Boston, MA. https://doi.org/10.1007/0-387-24555-3_4
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DOI: https://doi.org/10.1007/0-387-24555-3_4
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-24554-6
Online ISBN: 978-0-387-24555-3
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