dks {dks} | R Documentation |
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.
dks(P,alpha=c(0.1,10),beta=c(0.1,10),plot=TRUE,eps=1e-10)
P |
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. |
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.
dkspvalue |
The double Kolmogorov-Smirnov p-value. |
postprob |
A B-vector of the posterior probability that each study's null p-values are uniform. |
Jeffrey T. Leek jleek@jhsph.edu
J.T. Leek and J.D. Storey, "The Joint Null Distribution of Multiple Hypothesis Tests."
pprob.uniform
, dks.pvalue
, pprob.dist
,cred.set
## Load data data(dksdata) ## Perform the diagnostic tests with plots dks1 <- dks(P) dks1$dkspvalue