# Suppose that two formulations of a drug are to be compared
# on the regular scale using a two-period crossover design,
# with theta1 = -0.20, theta2 = 0.20, rm(CV) = 0.20, and
# we choose
n<-c(9,12,18,24,30,40,60)
# corresponding to
nu<-c(7,10,16,22,28,38,58)
# degrees of freedom. We need to test bioequivalence at the
# .05 significance level, which corresponds to having a .90 confidence
# interval lying within (-0.20, 0.20). This corresponds to
# Phillips (1990), Figure 3. Use
power.equivalence.md.plot(.05, FALSE, -.2, .2, .20, n, nu, 'Phillips Figure 3')
# If the formulations are compared on the logarithmic scale with
# theta1 = 0.80, theta2 = 1.25, and
n<-c(8,12,18,24,30,40,60)
# corresponding to
nu<-c(6,10,16,22,28,38,58)
# degrees of freedom. This corresponds to Diletti, Figure 1c. Use
power.equivalence.md.plot(.05, TRUE, .8, 1.25, .20, n, nu, 'Diletti, Figure 1c')
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