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simtrial - Clinical Trial Simulation

Provides some basic routines for simulating a clinical trial. The primary intent is to provide some tools to generate trial simulations for trials with time to event outcomes. Piecewise exponential failure rates and piecewise constant enrollment rates are the underlying mechanism used to simulate a broad range of scenarios such as those presented in Lin et al. (2020) <doi:10.1080/19466315.2019.1697738>. However, the basic generation of data is done using pipes to allow maximum flexibility for users to meet different needs.

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cpp

10.23 score 39 stars 1 dependents 134 scripts 837 downloads

metalite.ae - Adverse Events Analysis Using 'metalite'

Analyzes adverse events in clinical trials using the 'metalite' data structure. The package simplifies the workflow to create production-ready tables, listings, and figures discussed in the adverse events analysis chapters of "R for Clinical Study Reports and Submission" by Zhang et al. (2022) <https://r4csr.org/>.

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cdiscclinical-trialsmetadata

10.21 score 28 stars 2 dependents 59 scripts 505 downloads

gsDesign2 - Group Sequential Design with Non-Constant Effect

The goal of 'gsDesign2' is to enable fixed or group sequential design under non-proportional hazards. To enable highly flexible enrollment, time-to-event and time-to-dropout assumptions, 'gsDesign2' offers piecewise constant enrollment, failure rates, and dropout rates for a stratified population. This package includes three methods for designs: average hazard ratio, weighted logrank tests in Yung and Liu (2019) <doi:10.1111/biom.13196>, and MaxCombo tests. Substantial flexibility on top of what is in the 'gsDesign' package is intended for selecting boundaries.

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cpp

9.10 score 34 stars 235 scripts 677 downloads

metalite - ADaM Metadata Structure

A metadata structure for clinical data analysis and reporting based on Analysis Data Model (ADaM) datasets. The package simplifies clinical analysis and reporting tool development by defining standardized inputs, outputs, and workflow. The package can be used to create analysis and reporting planning grid, mock table, and validated analysis and reporting results based on consistent inputs.

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cdiscclinical-trialsmetadata

9.06 score 18 stars 5 dependents 86 scripts 478 downloads

forestly - Interactive Forest Plot

Interactive forest plot for clinical trial safety analysis using 'metalite', 'lt', and Analysis Data Model (ADaM) datasets. Includes functionality for adverse event filtering, incidence-based group filtering, hover-over reveals, and search and sort operations. The workflow allows for metadata construction, data preparation, output formatting, and interactive plot generation.

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8.90 score 23 stars 38 scripts 476 downloads

metalite.sl - Subject-Level Analysis Using 'metalite'

Analyzes subject-level data in clinical trials using the 'metalite' data structure. The package simplifies the workflow to create production-ready tables, listings, and figures discussed in the subject-level analysis chapters of "R for Clinical Study Reports and Submission" by Zhang et al. (2022) <https://r4csr.org/>.

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6.81 score 2 stars 9 scripts 325 downloads

boxly - Interactive Box Plot

Interactive box plot using 'plotly' for clinical trial analysis.

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6.69 score 14 stars 7 scripts 359 downloads