gMCP (version 0.8-5)

Example Graphs: Functions that create different example graphs

Description

Functions that creates example graphs, e.g. graphs that represents a Bonferroni-Holm adjustment, parallel gatekeeping or special procedures from selected papers. We are providing functions and not the resulting graphs directly because this way you have additional examples: You can look at the function body with body and see how the graph is built.

Usage

BonferroniHolm(n)
	parallelGatekeeping()
	improvedParallelGatekeeping()
	BretzEtAl2011()
	HungEtWang2010()
	HuqueAloshEtBhore2011()
	HommelEtAl2007()
	HommelEtAl2007Simple()
	MaurerEtAl1995()
	improvedFallbackI(weights=rep(1/3, 3))
	improvedFallbackII(weights=rep(1/3, 3))
	cycleGraph(nodes, weights)
	fixedSequence(n)
	fallback(weights)
	generalSuccessive(weights = c(1/2, 1/2))
	simpleSuccessiveI()
	simpleSuccessiveII()
	truncatedHolm()
	BauerEtAl2001()
	BretzEtAl2009a()
	BretzEtAl2009b()
	BretzEtAl2009c()
	Ferber2011()
	FerberTimeDose2011(times, doses, w="\\nu")
	Entangled1Maurer2012()
	Entangled2Maurer2012()

Arguments

n

Number of hypotheses.

nodes

Character vector of node names.

weights

Numeric vector of node weights.

times

Number of time points.

doses

Number of dose levels.

w

Further variable weight(s) in graph.

Value

• A graph of class graphMCP that represents a sequentially rejective multiple test procedure.

Details

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

References

Holm, S. (1979). A simple sequentally rejective multiple test procedure. Scandinavian Journal of Statistics 6, 65-70.

Dmitrienko, A., Offen, W., Westfall, P.H. (2003). Gatekeeping strategies for clinical trials that do not require all primary effects to be significant. Statistics in Medicine. 22, 2387-2400.

Bretz, F., Maurer, W., Brannath, W., Posch, M.: A graphical approach to sequentially rejective multiple test procedures. Statistics in Medicine 2009 vol. 28 issue 4 page 586-604. http://www.meduniwien.ac.at/fwf_adaptive/papers/bretz_2009_22.pdf

Bretz, F., Maurer, W. and Hommel, G. (2011), Test and power considerations for multiple endpoint analyses using sequentially rejective graphical procedures. Statistics in Medicine, 30: 1489--1501.

Hommel, G., Bretz, F. und Maurer, W. (2007). Powerful short-cuts for multiple testing procedures with special reference to gatekeeping strategies. Statistics in Medicine, 26(22), 4063-4073.

Hommel, G., Bretz, F. (2008): Aesthetics and power considerations in multiple testing - a contradiction? Biometrical Journal 50:657-666.

Hung H.M.J., Wang S.-J. (2010). Challenges to multiple testing in clinical trials. Biometrical Journal 52, 747-756.

W. Maurer, L. Hothorn, W. Lehmacher: Multiple comparisons in drug clinical trials and preclinical assays: a-priori ordered hypotheses. In Biometrie in der chemisch-pharmazeutischen Industrie, Vollmar J (ed.). Fischer Verlag: Stuttgart, 1995; 3-18.

Maurer, W., & Bretz, F. (2012). Memory and other properties of multiple test procedures generated by entangled graphs. Statistics in medicine.

Wiens, B.L., Dmitrienko, A. (2005): The fallback procedure for evaluating a single family of hypotheses. Journal of Biopharmaceutical Statistics 15:929-942.

Ferber, G. Staner, L. and Boeijinga, P. (2011): Structured multiplicity and confirmatory statistical analyses in pharmacodynamic studies using the quantitative electroencephalogram, Journal of neuroscience methods, Volume 201, Issue 1, Pages 204-212.

Examples

g <- BonferroniHolm(5)

# If Rgraphviz is installed, we can take a look at the graph:
library(Rgraphviz)
renderGraph(layoutGraph(g))

gMCP(g, pvalues=c(0.1, 0.2, 0.4, 0.4, 0.7))