Create Common Tables and Listings Used in Clinical Trials

Structure and formatting requirements for clinical trial table and listing outputs vary between pharmaceutical companies. 'junco' provides additional tooling for use alongside the 'rtables', 'rlistings' and 'tern' packages when creating table and listing outputs. While motivated by the specifics of Johnson and Johnson Clinical and Statistical Programming's table and listing shells, 'junco' provides functionality that is general and reusable. Major features include a) alternative and extended statistical analyses beyond what 'tern' supports for use in standard safety and efficacy tables, b) a robust production-grade Rich Text Format (RTF) and DOCX exporter for tables, listings and graphs, c) structural support for spanning column headers and risk difference columns in tables, and d) robust font-aware automatic column width algorithms for both listings and tables.

junco

Overview

The junco R package contains analysis functions to create tables and listings used for clinical trial reporting. It complements the tern package by providing additional statistical analysis capabilities.

The package provides a range of functionality, such as:

• Statistical analysis (ANCOVA, MMRM, Cox regression, Kaplan-Meier, CMH stratified proportion difference estimation)
• Calculation of odds ratios, relative risks, and proportion differences
• Event incidence rate analysis
• Support optional SAS (to-nearest-value) and IEC (to-nearest-even) rounding
• Frequency tabulations and summarizations
• Reference-based multiple imputation (RBMI) for handling missing data
• Production-ready RTF and DOCX exporter for listings and tables (see tt_to_tbldf and export_as_docx_j)
• Creation of tables, listings, and graphs (TLGs)

Installation

Either you can install the stable CRAN version

install.packages("junco") #CRAN Release

Or you can install the development version from GitHub:

require('remotes')
remotes::install_github("johnsonandjohnson/junco", ref = "dev") #for the rolling dev release

Usage

To understand how to use this package, please refer to the vignettes (also available on the pkgdown site). You can list them locally with:

browseVignettes(package = "junco")

Key vignettes and what they cover:

• Getting started with junco — overview and basic workflow
  • Article: https://johnsonandjohnson.github.io/junco/articles/junco.html
  • What you’ll learn: how to set up data, create common analyses, and produce TLG-ready outputs using core helpers. To understand how to use this package, please refer to the vignettes (also available on the pkgdown site). You can list them locally with:

browseVignettes(package = "junco")

Key vignettes and what they cover:

• Getting started with junco — overview and basic workflow

  • Article: https://johnsonandjohnson.github.io/junco/articles/junco.html
  • What you’ll learn: how to set up data, create common analyses, and produce TLG-ready outputs using core helpers.

• Table and listing customizations — controlling layouts and styles

  • Article: https://johnsonandjohnson.github.io/junco/articles/table_and_listing_customizations.html
  • What you’ll learn: how to customize headers, footers, column formatting, pagination, and how to export tables and listing to RTF and DOCX.

• Auto column widths — making table columns fit content automatically

  • Article: https://johnsonandjohnson.github.io/junco/articles/auto_colwidths.html
  • What you’ll learn: techniques and options for automatically sizing column widths for cleaner RTF/DOCX outputs.

TLG Catalog — browse examples and outputs

Explore a curated catalog of Tables, Listings, and Graphs (TLGs) generated with junco and companion tooling:

• TLG Catalog: https://johnsonandjohnson.github.io/TLG_Catalog

What you’ll find there:

• Realistic TLG outputs to help you preview what specific functions produce.
• Pointers to the underlying function calls and key arguments used to create each artifact.
• Context on when to use each approach (e.g., by analysis type or endpoint).

Tip: Use the catalog alongside the vignettes above and the function reference to quickly identify the right helper for your analysis, then adapt the showcased code to your study’s data and conventions.