| 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 | 2024-04-26 | 169 |
| Bayesian Inference | Jong Hee Park, Michela Cameletti, Xun Pang, Kevin M. Quinn | 2023-07-17 | 195 |
| Causal Inference | Imke Mayer, Pan Zhao, Noah Greifer, Nick Huntington-Klein, Julie Josse | 2023-08-04 | 152 |
| 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 | 55 |
| Cluster Analysis & Finite Mixture Models | Friedrich Leisch, Bettina Gruen | 2024-04-12 | 105 |
| 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 | 299 |
| Econometrics | Achim Zeileis, Grant McDermott, Kevin Tappe | 2023-08-08 | 153 |
| 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 | 102 |
| 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 | 92 |
| 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 | 2024-04-29 | 270 |
| Mixed, Multilevel, and Hierarchical Models in R | Ben Bolker, Julia Piaskowski, Emi Tanaka, Phillip Alday, Wolfgang Viechtbauer | 2022-10-31 | 156 |
| 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 | 2024-04-09 | 138 |
| Genomics, Proteomics, Metabolomics, Transcriptomics, and Other Omics | Julie Aubert, Toby Dylan Hocking, Nathalie Vialaneix | 2024-04-04 | 254 |
| Optimization and Mathematical Programming | Florian Schwendinger, Hans W. Borchers | 2024-03-17 | 138 |
| Analysis of Pharmacokinetic Data | Bill Denney | 2022-12-05 | 43 |
| 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 | 196 |
| 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 | 72 |
| Survival Analysis | Arthur Allignol, Aurelien Latouche | 2023-09-10 | 221 |
| 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 | 187 |
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.
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.