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gMCP (version 0.5-0)

gMCP: A graphical approach to sequentially rejective multiple test procedures

Description

Performs a sequentially rejective multiple test procedure on a graph given unadjusted p-values.

Usage

gMCP(graph, pvalues, test, correlation, alpha=0.05, ..., verbose=FALSE)

Arguments

graph
A graph of class graphMCP.
pvalues
A numeric vector specifying the p-values for the sequentially rejective MTP.
test
A test function. Will be supported in future versions.
correlation
Correlation matrix, if the tests are correlated. Also valid are strings like "Dunnett".
alpha
A numeric specifying the maximal allowed type one error rate.
...
Test specific arguments can be given here.
verbose
Logical scalar. If TRUE verbose output is generated during sequentially rejection steps.

Value

  • An object of class gMCPResult, more specifically a list with elements
  • graphslist of graphs
  • pvaluesp-values
  • rejectedlogical whether hyptheses could be rejected
  • adjPValuesadjusted p-values
  • If a correlation matrix is passed only the slots pvalues and rejected are set.

Details

For details see the given references.

References

Frank Bretz, Willi Maurer, Werner Brannath, Martin Posch: 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., Posch M., Glimm E., Klinglmueller F., Maurer W., Rohmeyer K. (2011): Graphical approaches for multiple endpoint problems using weighted Bonferroni, Simes or parametric tests - to appear.

Strassburger K., Bretz F.: Compatible simultaneous lower confidence bounds for the Holm procedure and other Bonferroni based closed tests. Statistics in Medicine 2008; 27:4914-4927.

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

Guilbaud O.: Simultaneous confidence regions corresponding to Holm's stepdown procedure and other closed-testing procedures. Biometrical Journal 2008; 50:678-692.

See Also

graphMCP

Examples

Run this code
g <- createBonferroniHolmGraph(5)

gMCP(g, pvalues=c(0.01, 0.02, 0.04, 0.04, 0.7))

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