Statistical Power Calculation
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Power in Clinical Trial: Superiority Design (Dichotomous outcome variable)
This utility can be used to calculate statistical power gained with given sample size for a clinical trial with superiority 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.
Superiority margin (d)
Required
It is the clinically significant margin to define superiority. Test arm proportion should be more than control arm proportion by this superiority margin to consider test intervention is superior to control intervention. It should be less than the actual absolute dfference between proportions in two arms. In percentage. (Between 0.01 to 99.99)
One sided test
Being a superiority design, hypothesis test is always one sided
Power ( 1 - β) =