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Test 1 Mean

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Test 1 Proportion

Compare 2 Proportions

Compare Paired Proportions

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Test Time-To-Event Data

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Test Relative Incidence in Self Controlled Case Series Studies

This calculator is useful for tests comparing paired proportions. Suppose that our sample consists of pairs of subjects, and that each pair contains a subject from group 'A' and a subject from group 'B'. Further suppose that we wish to compare the probability that an event occurs in group 'A' to that in group 'B'. Example study designs include matched case-control studies and cross-over studies. Conceptually, the data can be listed as in the following table.

Group 'B' | |||

Success | Failure | ||

Group 'A' | Success | $n_{11}$ | $n_{10}$ |

Failure | $n_{01}$ | $n_{00}$ |

Here, $n_{ij}$ represents the number of pairs having $i$ successes in Group 'A' and $j$ successes in Group 'B'. The corresponding proportions are denoted $p_{ij}$, with table

Group 'B' | |||

Success | Failure | ||

Group 'A' | Success | $p_{11}$ | $p_{10}$ |

Failure | $p_{01}$ | $p_{00}$ |

Interest is in comparing the following hypotheses:

$H_1:$The success probability is not equal between the Groups

Mathematically, this can be represented as

$H_1:p_{10}\neq p_{01}$

In the formulas below, we use the notation that

and

This calculator uses the following formulas to compute sample size and power, respectively:
$$
n=\left(\frac{z_{1-\alpha/2}\sqrt{p_{disc}}+z_{1-\beta}\sqrt{p_{disc}-p_{diff}^2}}{p_{diff}}\right)^2$$

$$1-\beta=\Phi\left(\frac{p_{diff}\sqrt{n}-z_{1-\alpha/2}\sqrt{p_{disc}}}{\sqrt{p_{disc}-p_{diff}^2}}\right)$$
where

- $n$ is sample size
- $\Phi$ is the standard Normal distribution function
- $\Phi^{-1}$ is the standard Normal quantile function
- $\alpha$ is Type I error
- $\beta$ is Type II error, meaning $1-\beta$ is power

R code to implement these functions:

p01=0.45 p10=0.05 alpha=0.05*2 # *2 to convert cited example's 1-sided test to 2-sided test beta=0.10 pdisc=p10+p01 pdiff=p10-p01 (n=((qnorm(1-alpha/2)*sqrt(pdisc)+qnorm(1-beta)*sqrt(pdisc-pdiff^2))/pdiff)^2) ceiling(n) # 23 x1=( pdiff*sqrt(n)-qnorm(1-alpha/2)*sqrt(pdisc))/sqrt(pdisc-pdiff^2); x2=(-pdiff*sqrt(n)-qnorm(1-alpha/2)*sqrt(pdisc))/sqrt(pdisc-pdiff^2); (Power = pnorm(x1)+pnorm(x2))

Connor R. J. 1987. Sample size for testing differences in proportions for the paired-sample design.Biometrics43(1):207-211.page 209.

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