In crossover designs, each subject receives a series of treatments
one after the other. Most papers on optimal crossover designs consider an
estimate which is corrected for carryover effects. We look at the estimate
for direct effects of treatment, which is not corrected for carryover effects.
If there are carryover effects, this estimate will be biased. We try to find a
design that minimizes the mean square error, that is the sum of the squared
bias and the variance. It turns out that the designs which are optimal for
the corrected estimate are highly efficient for the uncorrected estimate
