Announcing the Packages Hexwall

Interactive exploration of the Clinical Trials CRAN Task View

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Author

Yoni

Published

March 5, 2024

CRAN task views

The CRAN tasks views are an indispensable resource of information for discovering which R packages are the right ones for specific tasks. There are 44 of task views spanning a variety of topics. Each topic has subject matter experts who maintain the lists of packages. Below is a summary table of all the CRAN task views showing the topic (with a link to it), the maintainers, the date it was last updated and the number of packages in the task view.

CRAN Task Views Summary Table
Topic Maintainers Last Updated Number of Packages
Actuarial Science Christophe Dutang, Vincent Goulet 2024-02-23 40
Agricultural Science Julia Piaskowski, Adam Sparks, Adrian Correndo 2024-03-06 163
Bayesian Inference Jong Hee Park, Michela Cameletti, Xun Pang, Kevin M. Quinn 2023-07-17 198
Causal Inference Imke Mayer, Pan Zhao, Noah Greifer, Nick Huntington-Klein, Julie Josse 2023-08-04 155
Chemometrics and Computational Physics Katharine Mullen 2024-01-29 96
Clinical Trial Design, Monitoring, and Analysis Ed Zhang, W. G. Zhang, R. G. Zhang 2021-12-29 56
Cluster Analysis & Finite Mixture Models Friedrich Leisch, Bettina Gruen 2024-04-02 104
Databases with R Yuan Tang, James Joseph Balamuta 2023-02-23 45
Differential Equations Thomas Petzoldt, Karline Soetaert 2023-08-22 34
Probability Distributions Christophe Dutang, Patrice Kiener, Bruce J. Swihart 2024-03-13 301
Econometrics Achim Zeileis, Grant McDermott, Kevin Tappe 2023-08-08 156
Analysis of Ecological and Environmental Data Gavin L. Simpson 2023-12-18 100
Epidemiology Thibaut Jombart, Matthieu Rolland, Hugo Gruson 2024-03-18 88
Design of Experiments (DoE) & Analysis of Experimental Data Ulrike Groemping, Tyler Morgan-Wall 2023-04-05 103
Extreme Value Analysis Christophe Dutang 2023-11-04 41
Empirical Finance Dirk Eddelbuettel 2024-03-05 155
Functional Data Analysis Fabian Scheipl, Eleonora Arnone, Giles Hooker, J. Derek Tucker, Julia Wrobel 2022-03-21 41
Graphical Models Soren Hojsgaard 2023-04-05 38
High-Performance and Parallel Computing with R Dirk Eddelbuettel 2024-01-29 93
Hydrological Data and Modeling Sam Albers, Ilaria Prosdocimi 2024-03-08 130
Machine Learning & Statistical Learning Torsten Hothorn 2023-07-20 113
Medical Image Analysis Brandon Whitcher, Jon Clayden, John Muschelli 2022-08-31 32
Meta-Analysis Michael Dewey, Wolfgang Viechtbauer 2024-01-09 181
Missing Data Julie Josse, Imke Mayer, Nicholas Tierney, Nathalie Vialaneix 2024-01-29 273
Mixed, Multilevel, and Hierarchical Models in R Ben Bolker, Julia Piaskowski, Emi Tanaka, Phillip Alday, Wolfgang Viechtbauer 2022-10-31 158
Model Deployment with R Yuan Tang, James Joseph Balamuta 2022-08-24 31
Natural Language Processing Fridolin Wild 2023-09-12 60
Numerical Mathematics Hans W. Borchers, Robin Hankin, Serguei Sokol 2023-08-18 122
Official Statistics & Survey Statistics Matthias Templ, Alexander Kowarik, Tobias Schoch 2023-09-20 136
Genomics, Proteomics, Metabolomics, Transcriptomics, and Other Omics Julie Aubert, Toby Dylan Hocking, Nathalie Vialaneix 2024-04-04 256
Optimization and Mathematical Programming Florian Schwendinger, Hans W. Borchers 2024-03-17 139
Analysis of Pharmacokinetic Data Bill Denney 2022-12-05 45
Phylogenetics William Gearty, Brian O'Meara, Jacob Berv, Gustavo A. Ballen, Diniz Ferreira, Hilmar Lapp, Lars Schmitz, Martin R. Smith, Nathan S. Upham, Jonathan A. Nations 2024-01-30 103
Psychometric Models and Methods Patrick Mair, Yves Rosseel, Kathrin Gruber 2023-12-15 230
Reproducible Research John Blischak, Alison Hill, Ben Marwick, Daniel Sjoberg, Will Landau 2024-02-20 110
Robust Statistical Methods Martin Maechler 2023-07-01 53
Analysis of Spatial Data Roger Bivand, Jakub Nowosad 2024-02-21 195
Handling and Analyzing Spatio-Temporal Data Edzer Pebesma, Roger Bivand 2022-10-01 72
Sports Analytics Benjamin S. Baumer, Quang Nguyen, Gregory J. Matthews 2023-04-06 73
Survival Analysis Arthur Allignol, Aurelien Latouche 2023-09-10 222
Teaching Statistics Paul Northrop 2024-02-07 51
Time Series Analysis Rob J Hyndman, Rebecca Killick 2023-04-04 381
Processing and Analysis of Tracking Data Rocío Joo, Mathieu Basille 2023-03-07 49
Web Technologies and Services Mauricio Vargas Sepulveda, Will Beasley 2023-02-18 188

Clinical Trials task view

We are going to focus on the Clinical Trial Design, Monitoring, and Analysis task view maintained by Ed Zhang, W. G. Zhang, R. G. Zhang. Below is the task view itself. The task view layout has in the header summary information of the task view and the body contains the packages. They are categorized into sections: Design and Monitoring, Design and Analysis, Analysis for Specific Designs, Analysis in General and Meta Analysis.

The next area of the layout lists which packages are “Core” packages to the task view, which are “Regular” and which are archived on CRAN. There is a section listing related links that can include either noteworthy packages on GitHub or topic-specific references. Finally, there are links to other task views that the packages may intersect.

Each package listed in the task view has a link to the CRAN homepage of the package and a short description of what task the package intends to solve.

The Hexwall

This resource has a wealth of information for the newly initiated R user and also the expert R user in keeping up to date with the latest packages in the subject.

This being said the layout of the task view may be a bit daunting. It is strictly text and only gives a short description of each package. To fully understand what the package does and the health of the package the reader needs to click on the package link and then conduct more research to get relevant information.

This can be for many an entry cost that limits and inhibits the full utility of the task view and the hard work the maintainers do to keep it up to date.

To remedy these issues we have developed a new layout to navigate the packages listed in the task view. It is an interactive layout with packages represented as hex images, where we use the package hex sticker when there is one and a general hexagon for packages without. When the user clicks on a hex sticker the CRAN package homepage is displayed on the left-hand side.

Next Steps

This is the first release of the hexwall layout and we plan to iterate and add more useful information to it. We invite users to give us feedback on the layout and what information they would like to see added to it that will make your research into which packages to use to complete a task more informative and efficient.