Statistical Power Calculation
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Clinical Trial: Non-inferiority Design (Dichotomous outcome variable)
This utility can be used to calculate statistical power gained with given sample size for a clinical trial with non-inferiority 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
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.
Clinically Acceptable Margin for non-inferiority (d)
Required
It is the clinically significant margin to define non-inferiority. Test arm proportion should not be less than control arm proportion by this non-inferority margin to consider test intervention is non-inferior to control intervention. In percentage. (Between 0.01 to 99.99)
One sided test
Being a non-inferiority design, hypothesis test is always one sided
Power ( 1 - β) =