# Multiple.Testing: Multiple Testing procedures In TrialSize: R functions in Chapter 3,4,6,7,9,10,11,12,14,15

## Description

Ho: μ_{1j}-μ_{2j} = 0

Ha: μ_{1j}-μ_{2j} > 0

## Usage

 `1` ```Multiple.Testing(s1, s2, m, p, D, delta, BCS, pho, K, alpha, beta) ```

## Arguments

 `s1` We use bisection method to find the sample size, which let the equation h(n)=0. Here s1 and s2 are the initial value, 0 < s1 < s2. h(s1) should be smaller than 0. `s2` s2 is also the initial value, which is larger than s1 and h(s2) should be larger than 0. `m` m is the total number of multiple tests `p` p=n1/n. n1 is the sample size for group 1, n2 is the sample size for group 2, n=n1+n2. `D` D is the number of predictive genes. `delta` δ_j is the fix effect size among the predictive genes. We assume δ_j = delta, j =1,...,D and δ_j =0, j =D+1,....,m. `BCS` BCS means block compound symmetry, which is the length of each blocks. If we only have one block, BCS=m, which is refer to compound symmetry(CS). `pho` pho is the correlation parameter. If j and j' in the same block, ρ_{jj'}=pho ; otherwise ρ_{jj'} = 0 . `K` K is the number of replicates for the simulation. `alpha` here alpha is the adjusted Familywise error rate (FWER) `beta` here power is a global power. power=1-beta

## References

Chow SC, Shao J, Wang H. Sample Size Calculation in Clinical Research. New York: Marcel Dekker, 2003

TrialSize documentation built on May 30, 2017, 7:18 a.m.