newFocus: The new focus level procedure

In newFocus: True Discovery Guarantee by Combining Partial Closed Testings

Description

The new focus level procedure for calculating true discoveries for focus level nodes

Usage

newFocus(response, fsets, null, data, maxit = 0, alpha = 0.05, adj = 0)

Arguments

response	The response variable
fsets	A list of focus level sets
null	The null hypothesis
data	The data frame with response and all covariates included
maxit	The maximal number of repetitions prespecified by user
alpha	The significance level
adj	The number of focus sets that are fully rejected by partial closed testing, which is used to adjust the number of focus sets, The dafault value is 0.

Value

The function will return a focus subject with the lower bound for each focus level node.

Author(s)

Ningning Xu

References

Goeman, J. J., & Mansmann, U. (2008). Multiple testing on the directed acyclic graph of gene ontology. Bioinformatics, 24(4), 537-544.

Examples

## example data set
n= 100
m = 5
X = matrix(0, n, m,byrow = TRUE )
for ( i in 1:n){
  set.seed(1234+i)
  X[i,] =  as.vector(arima.sim(model = list(order = c(1, 0, 0), ar = 0.2), n = m) )
}
y = rbinom(n,1,0.6)
X[which(y==1),1:3] = X[which(y==1),1:3] + 0.8
xs = paste("x",seq(1,m,1),sep="") 
colnames(X) = xs

mydata = as.data.frame(cbind(X,y))

## focus level sets
fl = list(c("x1", "x2"), c("x3", "x4"), "x5")
names(fl) = c("12", "34", "5")

## get td for focus level sets
focus_subject = newFocus(response = y, fsets = fl, data = mydata)

## get td for any set of interest given the focus subject
setofinterest = c("x1", "x2","x3", "x4")
pick(focus_subject, setofinterest)

newFocus documentation built on July 5, 2021, 5:09 p.m.