dks: Frequentist and Bayesian diagnostic tests for multiple testing p-values.

Description

This function accepts a matrix of simulated null p-values where each column corresponds to the p-values from a single simulated study. The null p-values should represent a subset of all the simulated p-values corresponding to the tests with no signal.

Usage

dks(P,alpha=c(0.1,10),beta=c(0.1,10),plot=TRUE,eps=1e-10)

Arguments

An m0 x B matrix of null p-values, each column corresponds to the p-values from a single simulated study.

alpha

The range of the first parameter for the prior on the beta distribution.

beta

The range of the second parameter for the prior on the beta distribution.

plot

Should diagnostic plots be displayed.

eps

Maximum integration error when computing the posterior distribution.

Value

dkspvalue: The double Kolmogorov-Smirnov p-value.
postprob: A B-vector of the posterior probability that each study's null p-values are uniform.

Details

The dks function performs the Bayesian and Frequentist diagnostic tests outlined in Leek and Storey (2009). The result of the function is a double Kolmogorov-Smirnov p-value as well as posterior probability of uniformity estimates for each of the studies. The p-values should be simulated from a realistic distribution and only the null p-values should be passed to the dks function.

References

J.T. Leek and J.D. Storey, "The Joint Null Distribution of Multiple Hypothesis Tests."

Examples

Run this code


  ## Load data
  data(dksdata) 
  
  ## Perform the diagnostic tests with plots
  dks1 <- dks(P)
  dks1$dkspvalue

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