A Guided Tour of rtables - Intermediate
In rtables: Reporting Tables

suggested_dependent_pkgs <- c("dplyr")
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = all(vapply(
    suggested_dependent_pkgs,
    requireNamespace,
    logical(1),
    quietly = TRUE
  ))
)

knitr::opts_chunk$set(comment = "#")

Scope and Audience

Now that we have an understanding of how the rtables framework behaves mechanically from a user perspective, our next step is to build up intuition for how to leverage rtables' flexibility to create table outputs that go beyond simple straightforward structures.

This portion of the guide is intended for users with a reasonable grasp of what the individual layouting instructions do by default who want to learn how to combine and customize their behavior to achieve complex structured tables when a library of suitable analysis, group summary, and split functions is already available. It is a good fit for users looking to leverage, e.g., tern or junco to create tables without writing custom functions themselves.

Taking full control of tabulation behavior by creating our own functions, and understanding the layouting engine's default behavior will be covered in the upcoming advanced and introductory portions of this guide, respectively. In the meantime we refer readers looking for such content to the wide array of existing vignettes and documentation available beyond this guided tour.

Chapters

Translating Shells To Layouts - Identifying key structural features in a table shell and mapping them to rtables concepts
Identifying Required Analysis Behavior - Reasoning about analysis behaviors and choosing an afun
Identifying Required Faceting Behavior - Reasoning about faceting and choosing a split function