summary.p.fdr: Summary of p.fdr.object

In FDRestimation: Estimate, Plot, and Summarize False Discovery Rates

Summary of p.fdr.object

Description

This function summarizes a p.fdr object.

Usage

## S3 method for class 'p.fdr'
summary(object, digits = 5, ...)

Arguments

object	A list of output from the p.fdr function.
digits	A numeric value for the number of desired digits in the summary output. Defaults to 3.
...	Additional arguments affecting the summary produced.

Details

We run into errors or warnings when

Value

A list containing the following components:

Range	The range on the false discovery rates.
Significant Findings	The number of significant findings. Found using the adjusted p-values and the given threshold. This is also the number of times we decide to reject the null hypothesis that the data is generated from a standard normal distribution.
Inconclusive Findings	The number of inconclusive findings. Found using the adjusted p-values and the given threshold. This is also the number of times we fail to reject the null hypothesis that the data is generated from a standard normal distribution.
Assumed/Estimated pi0	the assumed or estimated pi0 value depending on how the p.fdr function was run.
Number of Tests	The total number of multiple comparison tests completed.
Adjustment Method	The adjustment method used in the p.fdr function.

References

\insertRef

Rpack:bibtexRdpack

\insertRef

RFDRestimation

\insertRef

murray2020falseFDRestimation

See Also

plot.p.fdr, p.fdr, get.pi0

Examples

# Example 1
pi0 = 0.8
pi1 = 1-pi0
n = 10
n.0 = ceiling(n*pi0)
n.1 = n-n.0

sim.data = c(rnorm(n.1,5,1),rnorm(n.0,0,1))
sim.data.p = 2*pnorm(-abs(sim.data))

fdr.output = p.fdr(pvalues=sim.data.p, adjust.method="BH")

summary(fdr.output)

FDRestimation documentation built on April 1, 2022, 5:07 p.m.