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Sample Size and Power Calculations |

In a test of equivalence, a treatment mean and a reference mean are compared to each other. Equivalence is taken to be the alternative hypothesis, and the null hypothesis is nonequivalence. The power of a test is the probability of rejecting the null hypothesis when the alternative is true, so in this case, the power is the probability of failing to reject equivalence when the treatments are in fact equivalent, that is, the treatment difference or ratio is within the prespecified boundaries.

The computational details for the power of an equivalence test (refer to Phillips 1990 for the additive model; Diletti, Hauschke, and Steinijans 1991 for the multiplicative) are as follows:

Owen (1965) showed that (*t _{1}*,

where is the quantile of a
*t* distribution with df.

and

For equivalence tests, alpha is usually set to 0.05, and power ranges from 0.70 to 0.90 (often set to 0.80).

For the **additive model** of equivalence, the values you must enter
for the null difference, the coefficient of variation (c.v.), and the
lower and upper bioequivalence limits must be expressed as percentages
of the reference mean. More information on specifications follow:

- Calculate the null difference as ,where is the hypothesized treatment mean and is the hypothesized reference mean. The null difference is often in the range of 0 to 0.20.
- For the coefficient of variation value, can be estimated by , where is the residual variance of the observations (MSE). Enter the c.v. as a percentage of the reference mean, so for the c.v., enter , or . This value is often in the range of 0.05 to 0.30.
- Enter the bioequivalence lower and upper limits as percentages of the reference mean as well. That is, for the bounds, enter and . These values are often -0.2 and 0.2, respectively.

For the **multiplicative model** of equivalence, calculate the null
ratio as , where is the hypothesized
treatment mean and is the hypothesized reference mean. This
value is often in the range of 0.80 to 1.20. More information on
specifications follow:

- The coefficient of variation (c.v.) is defined as .You can estimate by , where is the residual variance of the logarithmically transformed observations. That is, can be estimated by from the ANOVA of the transformed observations. The c.v. value is often in the range of 0.05 to 0.30.
- The bioequivalence lower and upper limits are often set to 0.80 and 1.25, respectively.

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