get_bh_threshold: Data-driven threshold of Benjamini Hochberg Procedure
In IHW: Independent Hypothesis Weighting
Description
Usage
Arguments
Value
Examples
Description
Given pvalues and a nominal significance level alpha, this function returns the
rejection threshold of the Benjamini-Hochberg procedure, i.e. a value t_BH such that p-values with
P_i <= t_BH get rejected by the procedure.
Usage
1
get_bh_threshold(pvals, alpha, mtests = length(pvals))
Arguments
pvals
Numeric, vector of p-values
alpha
Numeric in [0,1], significance level of the multiple testing procedure
mtests
Integer, total number of hypothesis tests; only set this (to non-default) when you know what you are doing!
Value
A numeric in [0,1], threshold of the BH procedure
Examples
1
2
3
4
pvalues <- c(runif(1000), rbeta(1000,0.5,7)) # generate some p-values
adj_pvalues <- p.adjust(pvalues, method="BH") # calculate adjusted p-values
t_BH <- get_bh_threshold(pvalues, 0.1) #get rejection threshold at alpha=0.1
all((pvalues <= t_BH) == (adj_pvalues <= 0.1)) #equivalence of two formulations
IHW documentation built on Nov. 8, 2020, 7:44 p.m.
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Description Usage Arguments Value Examples
Description
Given pvalues and a nominal significance level alpha, this function returns the rejection threshold of the Benjamini-Hochberg procedure, i.e. a value t_BH such that p-values with P_i <= t_BH get rejected by the procedure.
Usage
1 | get_bh_threshold(pvals, alpha, mtests = length(pvals))
|
Arguments
pvals |
Numeric, vector of p-values |
alpha |
Numeric in [0,1], significance level of the multiple testing procedure |
mtests |
Integer, total number of hypothesis tests; only set this (to non-default) when you know what you are doing! |
Value
A numeric in [0,1], threshold of the BH procedure
Examples
1 2 3 4 | pvalues <- c(runif(1000), rbeta(1000,0.5,7)) # generate some p-values
adj_pvalues <- p.adjust(pvalues, method="BH") # calculate adjusted p-values
t_BH <- get_bh_threshold(pvalues, 0.1) #get rejection threshold at alpha=0.1
all((pvalues <= t_BH) == (adj_pvalues <= 0.1)) #equivalence of two formulations
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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