Installation

Get arframe running in under two minutes

Install arframe

arframe is hosted on GitHub. The fastest way to install it is with pak:

# Install pak if you don't have it
install.packages("pak")

# Install arframe from GitHub
pak::pak("vthanik/arframe")

Or with remotes:

remotes::install_github("vthanik/arframe")

Install pharmaverseadam

The examples in this gallery use the pharmaverseadam package, which provides synthetic CDISC ADaM datasets (CDISCPILOT01 study, 135 subjects):

install.packages("pharmaverseadam")

Datasets used in this gallery: adsl, adae, adcm, advs, adlb, admh, adex, adeg, adrs_onco, adtte_onco, adtr_onco.

Optional: cards

The Path 2 (cards) examples use cards for ARD-based summarisation:

install.packages("cards")

Optional: Figure Dependencies

The figure examples (Kaplan-Meier, swimmer plot, waterfall plot) use additional packages:

install.packages(c("ggplot2", "survival", "broom", "scales", "patchwork"))

Utility: blank_to_na

The pharmaverseadam datasets contain SAS-style blank strings ("") that should be NA in R. Every example in this gallery uses this helper to convert them:

blank_to_na <- function(df) {
  df[] <- lapply(df, function(x) {
    if (is.character(x)) x[x == ""] <- NA_character_
    x
  })
  df
}

# Usage
adsl_saf <- pharmaverseadam::adsl |>
  blank_to_na() |>
  dplyr::filter(SAFFL == "Y", TRT01A != "Screen Failure")

This is included automatically in the hidden prerequisites of each example page.

Verify Your Installation

library(arframe)
library(pharmaverseadam)

# Quick sanity check — build and display a small table
adsl_saf <- adsl[adsl$SAFFL == "Y" & adsl$TRT01A != "Screen Failure", ]

adsl_saf[, c("TRT01A", "AGE", "SEX")] |>
  head(10) |>
  fr_table() |>
  fr_titles("Quick Check", "First 10 Safety Population Subjects") |>
  fr_cols(
    TRT01A = fr_col("Treatment", width = 2.5),
    AGE    = fr_col("Age",       width = 0.8, align = "center"),
    SEX    = fr_col("Sex",       width = 0.6, align = "center")
  ) |>
  fr_header(bold = TRUE, align = "center")

Minimal End-to-End Example

This is the smallest complete example that produces a publication-ready table:

library(arframe)
library(dplyr, warn.conflicts = FALSE)
library(pharmaverseadam)

adsl_saf <- adsl |>
  filter(SAFFL == "Y", TRT01A != "Screen Failure")

arm_levels <- c("Placebo", "Xanomeline Low Dose", "Xanomeline High Dose")

arm_n <- adsl_saf |>
  filter(TRT01A %in% arm_levels) |>
  count(TRT01A) |>
  pull(n, name = TRT01A)

age_wide <- adsl_saf |>
  filter(TRT01A %in% arm_levels) |>
  group_by(TRT01A) |>
  summarise(
    n          = as.character(n()),
    `Mean (SD)` = sprintf("%.1f (%.2f)", mean(AGE), sd(AGE)),
    Median     = sprintf("%.1f", median(AGE)),
    `Min, Max` = sprintf("%.0f, %.0f", min(AGE), max(AGE)),
    .groups    = "drop"
  ) |>
  tidyr::pivot_longer(-TRT01A, names_to = "Statistic", values_to = "val") |>
  tidyr::pivot_wider(names_from = TRT01A, values_from = val)

age_wide |>
  fr_table() |>
  fr_titles(
    "Table 1",
    "Age Summary",
    "Safety Population"
  ) |>
  fr_cols(
    Statistic = fr_col("Age (years)", width = 2.0),
    !!!setNames(
      lapply(arm_levels, function(a) fr_col(a, align = "decimal")),
      arm_levels
    ),
    .n = arm_n
  ) |>
  fr_header(bold = TRUE, align = "center") |>
  fr_footnotes("Safety Population: all subjects who received at least one dose.")

Render to PDF or RTF

Once you have a fr_spec object, render to any format with a single call:

# Assign the spec
spec <- age_wide |>
  fr_table() |>
  fr_titles("Table 1", "Age Summary", "Safety Population") |>
  fr_cols(
    Statistic = fr_col("Age (years)", width = 2.0),
    !!!setNames(
      lapply(arm_levels, function(a) fr_col(a, align = "decimal")),
      arm_levels
    ),
    .n = arm_n
  ) |>
  fr_header(bold = TRUE, align = "center")

# Three formats, zero code changes
out_pdf  <- file.path(tempdir(), "age_summary.pdf")
out_rtf  <- file.path(tempdir(), "age_summary.rtf")
out_html <- file.path(tempdir(), "age_summary.html")

spec |> fr_render(out_pdf)
spec |> fr_render(out_rtf)
spec |> fr_render(out_html)

on.exit(unlink(c(out_pdf, out_rtf, out_html)))

Study-Wide Theme

Set a theme once and it applies to every table in the session:

fr_theme(
  font_size   = 9,
  font_family = "Courier New",
  orientation = "landscape",
  hlines      = "header",
  n_format    = "{label}\n(N={n})",
  pagehead    = list(left = "Protocol: CDISCPILOT01", right = "CONFIDENTIAL"),
  pagefoot    = list(
    left  = "{program}",
    right = "Page {thepage} of {total_pages}"
  ),
  continuation = "(continued)"
)

# Reset when done
fr_theme_reset()

Rendering to PDF / RTF

Every fr_spec object can be rendered to PDF, RTF, or HTML with a single call. No code changes needed between formats:

spec |> fr_render("output.pdf")
spec |> fr_render("output.rtf")
spec |> fr_render("output.html")

PDF rendering requires XeLaTeX. See the arframe documentation for font setup details.

Next Steps

• Browse the Tables and Listings sections in the sidebar for examples.
• Each table page shows two data preparation approaches: manual dplyr and ARD-based cards.
• All examples use the pharmaverseadam CDISCPILOT01 synthetic datasets.