fdr.sampsize: Determine sample size required to achieve a desired average...

In FDRsampsize: Compute Sample Size that Meets Requirements for Average Power and FDR

Description

Determines the sample size needed to achieve a desired average power while controlling the FDR at a specified level.

Usage

fdr.sampsize (fdr, ave.pow, pow.func, eff.size, null.effect, max.n = 500, 
    min.n = 5, tol = 1e-05, eps = 1e-05, lam = 0.95, ...) 
## S3 method for class 'fdr.sampsize'
print(x,...)

Arguments

fdr	Desired FDR (scalar numeric)
ave.pow	Desired average power (scalar numeric)
pow.func	Character string name of function to compute power; must accept n, alpha, and eff.size as its first three arguments. Other optional arguments may also be provided.
eff.size	Numeric vector of effect sizes; interally, this will be provided as the third argument of pow.func
null.effect	Scalar value of the effect size under the null hypothesis. This may be 0 or 1 for tests that respectively use differences or ratios for comparisons.
max.n	Maximum n to consider
min.n	Minimum n to consider
tol	Tolerance for bisection calculations
eps	Epsilon for numerical differentiation
lam	Lambda for computing anticipated pi0 estimate, see Storey 2002.
x	result of the fdr.sampsize function
...	additional arguments for pow.func

Details

This function checks the technical conditions regarding whether the desired FDR can be achieved by min.n or max.n before calling n.fdr. Thus, for most applications, fdr.sampsize should be used instead of n.fdr.

Value

fdr.sampsize returns an object of class 'FDRsampsize', which is a list with the following components:

OK	indicates if the requirement is met
n	the computed sample size
alpha	the p-value threshold that gives the desired FDR
fdr.hat	anticipated value of the FDR estimate given n and effect size
act.fdr	actual expected FDR given n and effect size
ave.pow	average power
act.pi	actual value of pi0, the proportion of tests with a true null hypothesis.
pi.hat	expected value of the pi0 estimate
eff.size	input effect size vector

References

A Onar-Thomas, S Pounds. "FDRsampsize: An R package to Perform Generalized Power and Sample Size Calculations for Planning Studies that use the False Discovery Rate to Measure Significance", Manuscript 2015.

Pounds, Stan, and Cheng Cheng. "Sample size determination for the false discovery rate." Bioinformatics 21.23 (2005): 4263-4271.

Jung, Sin-Ho. "Sample size for FDR-control in microarray data analysis." Bioinformatics 21.14 (2005): 3097-3104.

Examples

 power.twosampt             # show the power.cox function
 res=fdr.sampsize(fdr=0.1,
                  ave.pow=0.8,
                  pow.func=power.twosampt,
                  eff.size=rep(c(1,0),c(10,990)),
                  null.effect=0)
 res
 

FDRsampsize documentation built on May 2, 2019, 9:14 a.m.