Software von Prof. Dr. Frank Bretz
- The gMCP package in R (main developer: Kornelius Rohmeyer) supports the visualization of graphical multiple test procedures and related sample size calculations. Alternatively, there is an R/gMCP bundle which contains all the essential files in one zip archive. See also the quick start guide for more information.
- The DoseFinding package in R (main developer: Bjoern Bornkamp) supports the design and analysis of dose finding studies. A description of a previous version of this software is given here.
- The multcomp package in R (main developer: Torsten Hothorn) allows one to perform multiple comparisons in general linear models. A short description of the package is given here. Details are given in:
Bretz, Hothorn and Westfall (2010) Multiple Comparisons Using R. Taylor and Francis, Boca Raton.
- Programs to calculate multivariate normal or t-probabilities using the approach of Genz (1992, 1993) and Genz and Bretz (1999, 2002):
SAS/IML program for multivariate t-probabilities.
Simple SAS/IML program for multivariate t-probabilities.
SAS/IML program for multivariate normal probabilities.
SAS application, which at run time calls executable files for the calculation of MVT probabilities.
There are also implementations available in MATLAB and with the mvtnorm package in R.
Details are given in:
Genz, Bretz (2009) Computation of Multivariate Normal and t Probabilities. Springer, Heidelberg.
- Programs for calculating orthant normal probabilities:
For small dimensions (k < 12) and tridiagonal correlation matrix click here.
For higher dimensions and/or more general correlation matrices click here.
For an algorithm to calculate level probabilities click here.
For estimating the minimum effective dose using the LRT of Bartholomew click here.
- Programs to calculate multivariate normal or t-probabilities using the approach of Somerville and Bretz (2001a, b):
Batch programs in FORTRAN or in SAS/IML.
Interactive programs in FORTRAN or in SAS/IML.
Exe-files of the batch or the interactive program.
- The daMA package contains functions for the efficient design and analysis of factorial two-colour microarray experiments.