Test whether the difference between the mean of the test population and the target is within the limits that you specify.
For example, an analyst wants to determine whether the mean strength of a generic drug is within ± 10 mg/ml of the target strength.
Test whether the mean of the test population is greater than the target.
For example, a food analyst wants to determine whether a less expensive formulation of a dry dog food has greater than 20 g of protein (per 100 g of food).
Test whether the mean of the test population is less than the target.
For example, an analyst wants to determine whether the mean time for a new medication to take effect is less than 5 minutes.
Test whether the difference between the mean of the test population and the target is greater than a lower limit.
For example, a researcher wants to determine whether an experimental drug induces a mean reduction in diastolic blood pressure that is greater than the expected reduction (target) by 3 mm Hg or more.
Test whether the difference between the mean of the test population and the target is less than an upper limit.
For example, an analyst wants to determine whether the mean waiting time in an emergency department is less than 10% over target.
Enter the lowest acceptable value for the difference. You want to demonstrate that the difference between the mean of the test population and the target is not lower than this value.
Enter the highest acceptable value for the difference. You want to demonstrate that the difference between the mean of the test population and the target does not exceed this value.
If you enter multiple values into a field, separate the values with a space. You can also use shorthand notation to indicate multiple values. For example, you can enter 10:40/5 to indicate sample sizes from 10 to 40 in increments of 5.
Sample sizes: Enter a sample size of interest. To assess the effect of different sample sizes, enter multiple values. Larger sample sizes give the test more power to demonstrate equivalence.
Differences (within the limits): Enter one or more values to specify the difference between the population mean and the target value. The value of the difference must be within the equivalence limits. Differences that are close to an equivalence limit require larger sample sizes to achieve adequate power.