_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-climatestability 0.1.4
Propagated dependencies: r-terra@1.7-83
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/hannahlowens/climateStability
Licenses: GPL 3
Synopsis: Estimating Climate Stability from Climate Model Data
Description:

Climate stability measures are not formalized in the literature and tools for generating stability metrics from existing data are nascent. This package provides tools for calculating climate stability from raster data encapsulating climate change as a series of time slices. The methods follow Owens and Guralnick <doi:10.17161/bi.v14i0.9786> Biodiversity Informatics.

r-clintrialpredict 0.0.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ClinTrialPredict
Licenses: Expat
Synopsis: Predicting and Simulating Clinical Trial with Time-to-Event Endpoint
Description:

Predict the course of clinical trial with a time-to-event endpoint for both two-arm and single-arm design. Each of the four primary study design parameters (the expected number of observed events, the number of subjects enrolled, the observation time, and the censoring parameter) can be derived analytically given the other three parameters. And the simulation datasets can be generated based on the design settings.

r-cliquepercolation 0.4.0
Propagated dependencies: r-qgraph@1.9.8 r-polychrome@1.5.1 r-pbapply@1.7-2 r-ohenery@0.1.2 r-matrix@1.7-1 r-magrittr@2.0.3 r-lessr@4.4.2 r-igraph@2.1.1 r-colorspace@2.1-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CliquePercolation
Licenses: GPL 3
Synopsis: Clique Percolation for Networks
Description:

Clique percolation community detection for weighted and unweighted networks as well as threshold and plotting functions. For more information see Farkas et al. (2007) <doi:10.1088/1367-2630/9/6/180> and Palla et al. (2005) <doi:10.1038/nature03607>.

r-clickableimagemap 1.0
Propagated dependencies: r-gtable@0.3.6 r-gridextra@2.3 r-ggplotify@0.1.2 r-ggplot2@3.5.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clickableImageMap
Licenses: GPL 2+
Synopsis: Implement 'tableGrob' Object as a Clickable Image Map
Description:

Implement tableGrob object as a clickable image map. The clickableImageMap package is designed to be more convenient and more configurable than the edit() function. Limitations that I have encountered with edit() are cannot control (1) positioning (2) size (3) appearance and formatting of fonts In contrast, when the table is implemented as a tableGrob', all of these features are controllable. In particular, the ggplot2 grid system allows exact positioning of the table relative to other graphics etc.

r-clinicalsignificance 2.1.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.2.1 r-rlang@1.1.4 r-purrr@1.0.2 r-lme4@1.1-35.5 r-insight@0.20.5 r-ggplot2@3.5.1 r-dplyr@1.1.4 r-cli@3.6.3 r-bayestestr@0.15.0 r-bayesfactor@0.9.12-4.7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://pedscience.github.io/clinicalsignificance/
Licenses: GPL 3+
Synopsis: Toolbox for Clinical Significance Analyses in Intervention Studies
Description:

This package provides a clinical significance analysis can be used to determine if an intervention has a meaningful or practical effect for patients. You provide a tidy data set plus a few more metrics and this package will take care of it to make your results publication ready. Accompanying package to Claus et al. <doi:10.18637/jss.v111.i01>.

r-clinicalutilityrecal 0.1.0
Propagated dependencies: r-nloptr@2.1.1 r-lattice@0.22-6 r-ggplot2@3.5.1 r-cowplot@1.1.3 r-caret@6.0-94
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ClinicalUtilityRecal
Licenses: GPL 2
Synopsis: Recalibration Methods for Improved Clinical Utility of Risk Scores
Description:

Recalibrate risk scores (predicting binary outcomes) to improve clinical utility of risk score using weighted logistic or constrained logistic recalibration methods. Additionally, produces plots to assess the potential for recalibration to improve the clinical utility of a risk model. Methods are described in detail in Mishra, A. (2019) "Methods for Risk Markers that Incorporate Clinical Utility" <http://hdl.handle.net/1773/44068>.

r-clinicaltrialsummary 1.1.1
Propagated dependencies: r-rcpp@1.0.13-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ClinicalTrialSummary
Licenses: GPL 3+
Synopsis: Summary Measures for Clinical Trials with Survival Outcomes
Description:

This package provides estimates of several summary measures for clinical trials including the average hazard ratio, the weighted average hazard ratio, the restricted superiority probability ratio, the restricted mean survival difference and the ratio of restricted mean times lost, based on the short-term and long-term hazard ratio model (Yang, 2005 <doi:10.1093/biomet/92.1.1>) which accommodates various non-proportional hazards scenarios. The inference procedures and the asymptotic results for the summary measures are discussed in Yang (2018, <doi:10.1002/sim.7676>).

Page: 123
Total results: 55