Package: c212 1.0.1

c212: Methods for Detecting Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes)

Provides a self-contained set of methods to aid clinical trial safety investigators, statisticians and researchers, in the early detection of adverse events using groupings by body-system or system organ class. This work was supported by the Engineering and Physical Sciences Research Council (UK) (EPSRC) [award reference 1521741] and Frontier Science (Scotland) Ltd. The package title c212 is in reference to the original Engineering and Physical Sciences Research Council (UK) funded project which was named CASE 2/12.

Authors:Raymond Carragher [aut, cre]

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c212.pdf |c212.html✨
c212/json (API)

# Install 'c212' in R:
install.packages('c212', repos = c('https://rcarragh.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/rcarragh/c212/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

4.06 score 57 scripts 236 downloads 35 exports 2 dependencies

Last updated 19 days agofrom:a5c260aa60. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-win-x86_64NOTENov 04 2024
R-4.5-linux-x86_64NOTENov 04 2024
R-4.4-win-x86_64NOTENov 04 2024
R-4.4-mac-x86_64NOTENov 04 2024
R-4.4-mac-aarch64NOTENov 04 2024
R-4.3-win-x86_64NOTENov 04 2024
R-4.3-mac-x86_64NOTENov 04 2024
R-4.3-mac-aarch64NOTENov 04 2024

Exports:c212.1ac212.1a.interimc212.BBc212.BB.interimc212.BHc212.BH.adjust.pvalsc212.bin.testc212.BONFc212.convergence.diagc212.DFDRc212.err.cntrlc212.fisher.testc212.GBHc212.gen.initial.valuesc212.global.sim.paramsc212.hyper.paramsc212.interim.1a.hier2c212.interim.1a.hier3c212.interim.BB.hier2c212.interim.BB.hier3c212.interim.MLEc212.LSLc212.monitor.samplesc212.NOADJc212.plot.eot.datac212.plot.interim.datac212.plot.samplesc212.pointmass.weightsc212.print.convergence.summaryc212.print.summary.statsc212.pthetac212.sim.control.paramsc212.ssBHc212.summary.statsc212.TST

Dependencies:codalattice

Readme and manuals

Help Manual

Help pageTopics
Methods for the Detection of Safety Signals in Randomised Controlled Trials using Groupings.c212-package
Implementation of the Berry and Berry Three-Level Hierarchical Model without Point-Mass.c212.1a
A Two or Three-Level Hierarchical Body-system based Model for interim analysis without Point-Mass.c212.1a.interim
Implementation of the Berry and Berry Three-Level Hierarchical Model.c212.BB
A Two or Three-Level Hierarchical Body-system based Model for interim analysis with Point-Mass.c212.BB.interim
Implementation of Benjamini-Hochberg procedure for False Discovery Rate controlc212.BH
Benjamini-Hochberg procedure adjusted p-valuesc212.BH.adjust.pvals
Plot Raw Adverse Event Incidence Datac212.bin.test
Implementation of Bonferroni correction for error controlc212.BONF
Convergence Diagnostics of the Simulationc212.convergence.diag
Implementation of the Double False Discovery Rate for controlling the False Discovery Rate.c212.DFDR
Implementaion of Group Bonferroni-Hochberg procedure for control of the False Discovery Ratec212.err.cntrl
Fisher Test p-values for End of Trial Data Clinical Datac212.FDR.data
Fisher Exact Testc212.fisher.test
Implementaion of Group Bonferroni-Hochberg procedure for control of the False Discovery Ratec212.GBH
Generate a template simulation initial values.c212.gen.initial.values
Generate a template for the individual model parameter simulation control parameters.c212.global.sim.params
Generate a template for the individual model parameter simulation control parameters.c212.hyper.params
A Two-Level Hierarchical Body-system based Model for interim analysis without Point-Mass.c212.interim.1a.hier2
A Three-Level Hierarchical Body-system based Model for interim analysis without Point-Mass.c212.interim.1a.hier3
A Three-Level Hierarchical Body-system based Model for interim analysis with Point-Mass.c212.interim.BB.hier2
A Three-Level Hierarchical Body-system based Model for interim analysis with Point-Mass.c212.interim.BB.hier3
Poisson Maximum Likelihood Estimatorc212.interim.MLE
Implementaion of the least-slope estimator estimator (LSL) for the proportion of true null hypotheses.c212.LSL
Generate a template for choosing which samples to monitor.c212.monitor.samples
Unadjusted test of multiple hypotheses.c212.NOADJ
Plot Adverse Event Incidence Datac212.plot.eot.data
Plot Adverse Event Count Data for a Body-system by Intervalc212.plot.interim.data
Plot Posterior Distributionc212.plot.samples
Generate a template for the point-mass weightings.c212.pointmass.weights
Print a Summary of the Convergence Diagnostics of the Simulationc212.print.convergence.summary
Print the Summary Statistics of Posterior Distributionsc212.print.summary.stats
Reports the posterior probability that theta (the increase in the log-odds) is greater than zero for each Adverse Eventc212.ptheta
Generate a template for the individual model parameter simulation control parameters.c212.sim.control.params
Implementation of Subset Benjamini-Hochberg for False Discover Rate controlc212.ssBH
Summary Statistics for the Posterior Distributions in the model.c212.summary.stats
End of Trial Data Clinical Data for Adverse Event Incidencec212.trial.data
Interim analysis trial data.c212.trial.interval.data1
Interim analysis trial data.c212.trial.interval.data2
Implementaion of the two-stage estimator (TST) for the proportion of true null hypotheses.c212.TST