mtpOrd: Controlling the False Discovery Rate and and the Generalized...
In someMTP: Some Multiple Testing Procedures

Description Usage Arguments Value Author(s) References See Also Examples

Ordinal procedure controlling the FDR and the Generalized FWER

1
2
3

fdrOrd(p, q = .01, ord = NULL, GD=FALSE)
kfweOrd(p, k = 1, alpha = 0.01, ord = NULL, alpha.prime = alpha,
        J = qnbinom(alpha, k, alpha.prime), GD = FALSE)

`p`	vector of p-values
`ord`	Values on the basis of which the procedure select the hypotheses (following decreasing order). The vector have the same length of `p`. If `NULL` the natural ordering is considered.
`q`	average FDR level
`alpha`	global significance level
`k`	number of allowed errors in kFWE controls
`J`	number of allowed jumps befor stopping
`alpha.prime`	univariate alpha for single step Guo and Romano procedure
`GD`	Logic value. Should the correction for general dependence be applied?

The function returns an object of class someMTP.object.

`rej:`	a logical vector indicating whenever the related hypotesis have been rejected.
`p:`	the vector of p-values used in the call
`ord:`	The vector used to sort the p-values (decrasing).
`MTP:`	"fdrOrd" or "kfweOrd"
`GD:`	A logical value incating if the correction for General Dependence have been used or not.
`q:`	The level of controlled FDR.
`alpha:`	The level of controlled k-FWER
`alphaprime:`	The significance level of individual tests
`k:`	Number of allowed Errors
`J:`	Number of allowed Jumps

L. Finos and A. Farcomeni

L. Finos, A. Farcomeni (2011). k-FWER Control without p-value Adjustment, with Application to Detection of Genetic Determinants of Multiple Sclerosis in Italian Twins. Biometrics.

A. Farcomeni, L. Finos (2013). FDR Control with Pseudo-Gatekeeping Based on a Possibly Data Driven Order of the Hypotheses. Biometrics.

See also draw

	set.seed(17)
	x=matrix(rnorm(60),3,20)
	x[,1:10]=x[,1:10]+2 ##variables 1:10 have tests under H1
	ts=apply(x,2,function(x) t.test(x)$statistic)
	ps=apply(x,2,function(x) t.test(x)$p.value) #compute p-values
	m2=apply(x^2,2,mean)           #compute ordering criterion

	pOrd <- fdrOrd(ps,q=.05,ord=m2)   #ordinal Procedure
	pOrd
	draw(pOrd)	
	sum(p.adjust(ps,method="BH")<=.05)  #rejections with BH
	
	kOrd <- kfweOrd(ps,k=5,ord=m2)#ordinal procedure
	kOrd
	kOrdGD <- kfweOrd(ps,k=5,ord=m2,GD=TRUE)#ord. proc. (any dependence)
	kOrdGD