power.density.equivalence.md  R Documentation 
A function to calculate density for the power of the two onesided tests prodedure (TOST). (See package equivalence
, function tost
.)
power.density.equivalence.md(power_sigma, alpha = alpha, theta1 = theta1,
theta2 = theta2, diff = diff, sigma = sigma, n = n, nu = nu)
power_sigma 
xvalue for integration 
alpha 

theta1 
lower limit of equivalence interval on appropriate scale (regular or log) 
theta2 
upper limit of equivalence interval on appropriate scale 
diff 
true difference (ratio on log scale) in treatment means on appropriate scale 
sigma 
sqrt(error variance) as fraction (i.e., square root of the mean square error from ANOVA, or coefficient of variation) 
n 
number of participants per treatment (number of total subjects for crossover design) 
nu 
degrees of freedom for sigma 
power_density 
density at diff for power of TOST: the probability that the confidence interval will lie within ['theta1', 'theta2'] 
Kem Phillips; kemphillips@comcast.net
Diletti, E., Hauschke D. & Steinijans, V.W. (1991). Sample size determination of bioequivalence assessment by means of confidence intervals, International Journal of Clinical Pharmacology, Therapy and Toxicology, 29, No. 1, 1–8.
Phillips, K.F. (1990). Power of the Two OneSided Tests Procedure in Bioquivalence, Journal of Pharmacokinetics and Biopharmaceutics, 18, No. 2, 139–144.
Schuirmann, D.J. (1987). A comparison of the two onesided tests procedure and the power approach for assessing the equivalence of average bioavailability, Journal of Pharmacokinetics and Biopharmaceutics, 15. 657–680.
power.equivalence.md.plot
, power.density.equivalence.md
## Not run:
# This function is called by power.equivalence.md within
# the integrate function. It is integrated over
# appropriate limits to compute the power. Use
power.density.equivalence.md(.1, alpha=.05, theta1=.2, theta2=.2, diff=.05,
sigma= .20, n=24, nu=22)
# The usage for the logarithmic scale is the same, except that
# theta1, theta2, and diff must be on that scale. That is, use log(.8), etc.
## End(Not run)
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