R(>= 2.10.0), stats, graphics, robustbase, RColorBrewer

R(>= 2.11.0), stats, graphics, robustbase, RColorBrewer

R(>= 2.14.0), stats, graphics, robustbase, RColorBrewer

person("Matthias", "Kohl", role = c("aut", "cre"),
email = "Matthias.Kohl@stamats.de")

Contains several functions for statistical data analysis; e.g. for sample size and power calculations, computation of confidence intervals, and generation of similarity matrices.

stats, graphics, grDevices, RColorBrewer, robustbase

stats, graphics, grDevices, RColorBrewer, robustbase, ggplot2
gplots, Amelia, knitr, rmarkdown, exactRankTests

stats, graphics, grDevices, RColorBrewer, robustbase, ggplot2,
scales
gplots, Amelia, knitr, rmarkdown, exactRankTests, foreach,
parallel, doParallel

stats, utils, graphics, grDevices, RColorBrewer, robustbase,
ggplot2, scales, limma
Contains several functions for statistical data analysis; e.g. for sample size and power calculations, computation of confidence intervals and tests, and generation of similarity matrices.

stats, utils, graphics, grDevices, RColorBrewer, robustbase,
limma
Similarity plots based on correlation and median absolute deviation (MAD); adjusting colors for heatmaps; aggregate technical replicates; calculate pairwise fold-changes and log fold-changes; compute one- and two-way ANOVA; simplified interface to package 'limma' (Ritchie et al. (2015), <doi:10.1093/nar/gkv007> ) for moderated t-test and one-way ANOVA; Hamming and Levenshtein (edit) distance of strings as well as optimal alignment scores for global (Needleman-Wunsch) and local (Smith-Waterman) alignments with constant gap penalties (Merkl and Waack (2009), ISBN:978-3-527-32594-8).

stats, utils, graphics, grDevices, RColorBrewer, robustbase,
limma, grid, circlize, ComplexHeatmap

stats, matrixTests, ggplot2, MKdescr, MKinfer(>= 0.4),
qqplotr, coin
Power analysis and sample size calculation for Welch and Hsu (Hedderich and Sachs (2018), ISBN:978-3-662-56657-2) t-tests including Monte-Carlo simulations of empirical power and type-I-error. Power and sample size calculation for Wilcoxon rank sum and signed rank tests via Monte-Carlo simulations. Power and sample size required for the evaluation of a diagnostic test(-system) (Flahault et al. (2005), <doi:10.1016/j.jclinepi.2004.12.009>; Dobbin and Simon (2007), <doi:10.1093/biostatistics/kxj036>) as well as for a single proportion (Fleiss et al. (2003), ISBN:978-0-471-52629-2) and comparing two negative binomial rates (Zhu and Lakkis (2014), <doi:10.1002/sim.5947>).