holm | R Documentation |
Holm's step-down-procedure is applied to pValues. It controls the FWER in the strong sense under arbitrary dependency.
holm(pValues, alpha, silent=FALSE)
pValues |
pValues to be used. They can have arbitrary dependency structure. |
alpha |
The level at which the FWER shall be controlled |
silent |
If true any output on the console will be suppressed. |
Holm's procedure uses the same critical values as Hochberg's procedure, namely c(i)=alpha/(m-i+1), but is a step-down version while Hochberg's method is a step-up version of the Bonferroni test. Holm's method is based on the Bonferroni inequality and is valid regardless of the joint distribution of the test statistics, whereas Hochberg's method relies on the assumption that Simes' inequality holds for the joint null distribution of the test statistics. If this assumption is met, Hochberg's step-up procedure is more powerful than Holm's step-down procedure.
A list containing:
adjPValues |
A numeric vector containing the adjusted pValues |
rejected |
A logical vector indicating which hypotheses are rejected |
criticalValues |
A numeric vector containing critical values used in the step-down test |
errorControl |
A Mutoss S4 class of type |
MarselScheer
S. Holm (1979). A simple sequentially rejective multiple
test procedure. Scand. J. Statist. Vol. 6, 65-70. n
Huang, Y. and Hsu, J. (2007). Hochberg's step-up method: cutting corners off Holm's step-down method. Biometrika, 94(4):965-975.
r <- c(runif(50), runif(50, 0, 0.01))
result <- holm(r, 0.05)
result <- holm(r, 0.05, silent = TRUE)
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