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teal.modules.clinical

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GitHub commit activity GitHub contributors GitHub last commit GitHub pull requests GitHub repo size GitHub language count Project Status: Active -- The project has reached a stable, usable state and is being actively developed. Current Version Open Issues

This package contains a set of standard teal modules to be used with CDISC data in order to generate many of the standard outputs used in clinical trials.

These modules include, but are not limited to:

  • Data visualizations:
    • Forest plots (tm_g_forest_rsp()/tm_g_forest_tte())
    • Line plots (tm_g_lineplot())
    • Kaplan-Meier plots (tm_g_km())
    • ...
  • Statistical model fits:
    • MMRM (tm_a_mmrm())
    • Logistic regression (tm_t_logistic())
    • Cox regression (tm_t_coxreg())
    • ...
  • Summary tables:
    • Unique patients (tm_t_summary())
    • Exposure across patients (tm_t_exposure())
    • Change from baseline for parameters (tm_t_summary_by())
    • ...
  • Patient-level profile modules:
    • Table of basic information about chosen patient (tm_t_pp_basic_info())
    • Plot of patient vitals over time (tm_g_pp_vitals())
    • General timeline for individual patients (tm_g_pp_patient_timeline())
    • ...

Most modules in the package are implemented using functions from the R package tern in order to produce their output.

Please see the Teal Gallery and TLG Catalog for examples of shiny apps created using modules from this package.

Installation

install.packages('teal.modules.clinical')

Alternatively, you might want to use the development version.

# install.packages("pak")
pak::pak("insightsengineering/teal.modules.clinical")

Usage

To understand how to use this package, please refer to the Getting Started article, which provides multiple examples of code implementation.

Playground

You can try out the package without installing it in the Shinylive:

Getting help

If you encounter a bug or have a feature request, please file an issue. For questions, discussions, and staying up to date, please use the teal channel in the pharmaverse slack workspace.

Acknowledgment

This package is the result of the joint efforts of many developers and stakeholders. We would like to thank everyone who has contributed so far!

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