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MultXpert package

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Return to Implementation of Multiple Testing Procedures.

Description

MultXpert R package provides software implementation of commonly used p-value-based and parametric multiple testing procedures and gatekeeping procedures.

Development team

Alex Dmitrienko, Eric Nantz and Gautier Paux with contributions by Thomas Brechenmacher.

Releases

Release 1

The MultXpert package (Release 1) was finalized on Jan 23, 2011. This release can be downloaded from the CRAN web site.

The following five functions are included in Release 1:

PValAdjP function computes adjusted p-values and generates decision rules for the Bonferroni, Holm (Holm, 1979), Hommel (Hommel, 1988), Hochberg (Hochberg, 1988), fixed-sequence (Westfall and Krishen, 2001) and fallback (Wiens, 2003; Wiens and Dmitrienko, 2005) procedures. The adjusted p-values are computed using the closure principle (Marcus, Peritz and Gabriel, 1976) in general hypothesis testing problems (equally or unequally weighted null hypotheses). The decision rules are generated only in hypothesis testing problems with equally weighted null hypotheses.

PValCI function computes one-sided simultaneous confidence limits for the Bonferroni, Holm (Holm, 1979) and fixed-sequence (Westfall and Krishen, 2001) procedures in in general one-sided hypothesis testing problems (equally or unequally weighted null hypotheses). The simultaneous confidence intervals are computed using the methods developed in Hsu and Berger (1999), Strassburger and Bretz (2008) and Guilbaud (2008).

ParAdjP function computes adjusted p-values for the single-step Dunnett procedure (Dunnett, 1955) and step-down Dunnett procedure (Naik, 1975; Marcus, Peritz and Gabriel, 1976) in one-sided hypothesis testing problems with a balanced one-way layout and equally weighted null hypotheses.

ParCI function computes one-sided simultaneous confidence limits for the single-step Dunnett procedure (Dunnett, 1955) and step-down Dunnett procedure (Naik, 1975; Marcus, Peritz and Gabriel, 1976) in one-sided hypothesis testing problems with a balanced one-way layout and equally weighted null hypotheses. The simultaneous confidence intervals are computed using the methods developed in Bofinger (1987) and Stefansson, Kim and Hsu (1988).

ParGateAdjP function computes adjusted p-values and generates decision rules for multistage parallel gatekeeping procedures in hypothesis testing problems with multiple families of null hypotheses (null hypotheses are assumed to be equally weighted within each family) based on the methodology presented in Dmitrienko, Tamhane and Wiens (2008) (see Dmitrienko Tamhane Wiens 2008) and Dmitrienko, Kordzakhia and Tamhane (2011) (see Dmitrienko Kordzakhia Tamhane 2011).

Other procedures

To find out more about software implementation of other multiple testing procedures and gatekeeping procedures, see Software.