Depends: R (>= 3.5.0), bnlearn, ClustOfVar, PCAmixdata, arules, zoo
Imports: PRROC, MLmetrics, rlist, stats, magrittr, visNetwork, plyr,

Title: Inferring Group Bayesian Networks using Hierarchical Feature
Authors@R: c(person("Ann-Kristin", "Becker", email = "annkristinbecker@web.de", role = c("aut", "cre")),
person("Lars", "Kaderali", email="lars.kaderali@uni-greifswald.de", role=c("aut", "ths")))
Description: Group Bayesian Networks: This package implements the inference of group Bayesian networks based on hierarchical feature clustering, and the adaptive refinement of the grouping regarding an outcome of interest, as described in Becker et. al (2021) <doi: 10.1371/journal.pcbi.1008735>.

Title: Paired/Unpaired Parametric/Non-Parametric Group Comparisons
Description: Receives two vectors, computes appropriate function for group comparison (i.e., t-test, Mann-Whitney; equality of variances), and reports the findings (mean/median, standard deviation, test statistic, p-value, effect size) in APA format (Fay, M.P., & Proschan, M.A. (2010)<DOI: 10.1214/09-SS051>).

Package: GroupSeq
Title: Performing computations related to groupseqential boundaries.
Version: 1.0
Author: Roman Pahl
Description: The computations are done with the alpha spending approach. Therefore
interim analyses need not to be equally spaced, and their number need not to be specified in advance.
It is appropriate for any trial based on normally distributed test statistics with independent increments,
survival studies, and certain longitudinal designs.
Among other things it computes boundaries, power, drift and confidence intervals.
The package provides this in a GUI and user has option of graphical output of the results
and saving them into .html files.
Maintainer: Roman Pahl <projects.pahl@web.de>
License: GNU GENERAL PUBLIC LICENSE - Version 2, June 1991
Packaged: Wed Feb  8 12:58:23 2006; hornik

Package: GroupSeq
Title: Performing computations related to groupseqential boundaries.
Version: 1.1
Author: Roman Pahl
Description: The computations are done via the alpha spending approach i.e. interim
analyses need not to be equally spaced, and their number need not to be specified in advance.
It is appropriate for any trial based on normally distributed test statistics with independent
increments, survival studies, and certain longitudinal designs.
Among other things it computes critical boundaries for various spending functions and for prespecified
power and drift. Confidence intervals are also obtained.
The package provides this in a GUI and users have option of graphical output of the results
and/or saving desings into .html-file tables allowing further processing.
Maintainer: Roman Pahl <projects.pahl@web.de>
License: GPL Version 2 or later.
Packaged: Wed Apr 19 21:10:43 2006; soLidas