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Fisher's Test of Proportions

The two sample test of proportions compares the proportions of two arms of a study, \(p_1\) and \(p_2\).

Note: There does not exist a closed form formula for the power of the bionomial test so this calculator uses simulations to solve for power. For large sample sizes, large sample theory can be used.

Power Calculation Parameters

To input multiple values, seperate them by a comma.

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Power Calculation Explanation

Solve For
The unknown you are interested in solving for.
N
The sample size used to test the hypothesis.
Alpha
The \(\alpha\) (Type I error rate) level of the hypothesis test.
Power
The power (1 - Type II error rate) of the hypothesis test.
P (Arm 1)
The estimated proportion from arm 1 (\(p_1\)). If you are comparing a difference in proportions to zero, set this value to the difference.
P (Arm 2)
The estimated proportion from arm 2 (\(p_2\)). If you are comparing a difference in proportions to zero, set this value to zero.

Calculation Results

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N (Arm 1) N (Arm 2) Alpha Power Proportion (Arm 1) Proportion (Arm 2) Margin
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Power Graph

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References

  • Chow, S., Shao, J., & Wang, H. (2003), Sample size calculations in clinical research, New York: Marcel Dekker.