Statistical Power Calculation
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Power in Clinical Trial: Equivalence Design (Dichotomous outcome variable)
This utility can be used to calculate statistical power gained with given sample size for a clinical trial with equivalence design and the outcome variable is dichotomous.
Formula used and other details
Number of participant with desired outcome in test arm (S1)
Enter positive number between 0 to 1000000
Required
Exact Number of successful outcomes in test arm.
Total Number of participant in test arm (N1)
Enter positive number between 1 to 1000000
Required
Sample size in test arm. Should be between 1 and 1000000
Number of participant with desired outcome in control arm (S2).
Enter positive number between 0 to 1000000
Required
Exact number of sucessful outcomes in control arm.
Total Number of participant in control arm (N2)
Enter positive number between 1 to 1000000
Required
Sample size in test arm. Should be between 1 and 1000000
Clinically Acceptable Margin for Equivalence (d)
Required
It is the clinically meaningful margin on either side of P2 to define equivalence of P1. Test arm proportion should be within control arm proportion by this equivalence margin to consider test intervention is equivalent to control intervention. In percentage. (Between 0.01 to 99.99)
Two sided test
Being an equivalence design, hypothesis test is always two sided. Calculations are done considering two one sided tests (TOST).
Confidence Level %
Enter positive number between 0.01 to 99.99
Required
In percentage. Commonly used values are 95, 99 and 90. Should be between 0.01 to 99.99.
Power ( 1 - β) =