EstimatedHFDRControl: Estimate FDR control variations for HFDR procedure

In krisrs1128/structSSI: Multiple Testing for Hypotheses with Hierarchical or Group Structure

Description

This function estimates two types of HFDR control appropriate for trees of hypotheses. If the BH procedure is applied at level alpha within each of the tree families, this is defined as

where a discovery is defined as an adjusted p value below alpha within the entire tree or at the tips for tree and tips FDR, respectively.

Usage

EstimatedHFDRControl(hyp.tree)

Arguments

hyp.tree

An object of class HypothesesTree, such as the result to a call of hFDR.adjust.

Details

Yekutieli, D. Hierarchical false discovery rate-controlling methodology. Journal of the American Statistical Association, 103(481):309-316, 2008. Benjamini, Y, and Yekutieli, D. Hierarchical fdr testing of trees of hypotheses. 2002. Sankaran, K and Holmes, S. structSSI: Simultaneous and Selective Inference for Grouped or Hierarchically Structured Data. Journal of Statistical Software, 59(13), 1-21. 2014. http://jstatsoft.org/v59/i13/

Value

A list with the following elements,

tree	The estimated full-tree FDR.
tip	The estimated outer-nodes FDR.
n.families.tested	The number of families of hypotheses tested by the HFDR procedure.
n.tree.discoveries	The number of discoveries over the whole tree.
n.tip.discoveries	The number of discoveries among the tree tips.

Examples

library("igraph")
library("ape")

alternative.indices <- sample(1:49, 30)
unadj.p.values <- vector("numeric", length = 49)
unadj.p.values[alternative.indices] <- runif(30, 0, 0.01)
unadj.p.values[-alternative.indices] <- runif(19, 0, 1)
unadj.p.values[c(1:5)] <- runif(5, 0, 0.01)
names(unadj.p.values) <- paste("Hyp ", c(1:49))

tree <- as.igraph(rtree(25))
V(tree)$name <- names(unadj.p.values)
tree.el <- get.edgelist(tree)

hyp.tree <- hFDR.adjust(unadj.p.values, tree.el, 0.05)

EstimatedHFDRControl(hyp.tree)

krisrs1128/structSSI documentation built on July 20, 2020, 9:42 a.m.