In ddsjoberg/gtsummary: Presentation-Ready Data Summary and Analytic Result Tables

knitr::opts_chunk$set(
  collapse = TRUE,
  warning = FALSE,
  comment = "#>"
)
gt_compact_fun <- function(x) {
  gt::tab_options(x,
    table.font.size = "small",
    data_row.padding = gt::px(1),
    summary_row.padding = gt::px(1),
    grand_summary_row.padding = gt::px(1),
    footnotes.padding = gt::px(1),
    source_notes.padding = gt::px(1),
    row_group.padding = gt::px(1)
  )
}

# we do NOT want the vignette to build on CRAN...it's taking too long
if (!identical(Sys.getenv("IN_PKGDOWN"), "true") &&
  !tolower(as.list(Sys.info())$user) %in% c("sjobergd", "currym", "whitingk", "whiting")) {
  msg <-
    paste(
      "View this vignette on the",
      "[package website](https://www.danieldsjoberg.com/gtsummary/articles/inline_text.html)."
    )
  cat(msg)
  knitr::knit_exit()
}

Introduction

Reproducible reports are an important part of good practices. We often need to report the results from a table in the text of an R markdown report. Inline reporting has been made simple with inline_text(). The inline_text() function reports statistics from {gtsummary} tables inline in an R markdown report.

Setup

Before going through the tutorial, install and load {gtsummary}.

# install.packages("gtsummary")
library(gtsummary)

Example data set

We'll be using the trial data set throughout this example.

• This set contains data from r nrow(trial) patients who received one of two types of chemotherapy (Drug A or Drug B). The outcomes are tumor response and death.

For brevity in the tutorial, let's keep a subset of the variables from the trial data set.

trial2 <-
  trial %>%
  select(trt, marker, stage)

Inline results from tbl_summary() {#inline_text_tbl_summary}

First create a basic summary table using tbl_summary() (review tbl_summary() vignette for detailed overview of this function if needed).

tab1 <- tbl_summary(trial2, by = trt)
tab1

To report the median (IQR) of the marker levels in each group, use the following commands inline.

The median (IQR) marker level in the Drug A and Drug B groups are `r inline_text(tab1, variable = marker, column = "Drug A")` and `r inline_text(tab1, variable = marker, column = "Drug B")`, respectively.

Here's how the line will appear in your report.

The median (IQR) marker level in the Drug A and Drug B groups are r inline_text(tab1, variable = marker, column = "Drug A") and r inline_text(tab1, variable = marker, column = "Drug B"), respectively.

If you display a statistic from a categorical variable, include the level argument.

`r inline_text(tab1, variable = stage, level = "T1", column = "Drug B")` resolves to "r inline_text(tab1, variable = stage, level = "T1", column = "Drug B")"

Inline results from tbl_regression() {#inline_text_tbl_regression}

Similar syntax is used to report results from tbl_regression() and tbl_uvregression() tables. Refer to the tbl_regression() vignette if you need detailed guidance on using these functions.

Let's first create a regression model.

# build logistic regression model
m1 <- glm(response ~ age + stage, trial, family = binomial(link = "logit"))

Now summarize the results with tbl_regression(); exponentiate to get the odds ratios.

tbl_m1 <- tbl_regression(m1, exponentiate = TRUE)
tbl_m1

To report the result for age, use the following commands inline.

`r inline_text(tbl_m1, variable = age)`

Here's how the line will appear in your report.

r inline_text(tbl_m1, variable = age)

It is reasonable that you'll need to modify the text. To do this, use the pattern argument. The pattern argument syntax follows glue::glue() format with referenced R objects being inserted between curly brackets. The default is pattern = "{estimate} ({conf.level*100}% CI {conf.low}, {conf.high}; {p.value})". You have access the to following fields within the pattern argument.

tibble::tribble(
  ~Parameter,       ~Description,
  "`{estimate}`",   "primary estimate (e.g. model coefficient, odds ratio)",
  "`{conf.low}`",   "lower limit of confidence interval",
  "`{conf.high}`",  "upper limit of confidence interval",
  "`{p.value}`",    "p-value",
  "`{conf.level}`", "confidence level of interval",
  "`{N}`",          "number of observations"
) %>%
  gt::gt() %>%
  gt::fmt_markdown(columns = c(Parameter)) %>%
  gt_compact_fun()

Age was not significantly associated with tumor response `r inline_text(tbl_m1, variable = age, pattern = "(OR {estimate}; 95% CI {conf.low}, {conf.high}; {p.value})")`.

Age was not significantly associated with tumor response r inline_text(tbl_m1, variable = age, pattern = "(OR {estimate}; 95% CI {conf.low}, {conf.high}; {p.value})").

If you're printing results from a categorical variable, include the level argument, e.g. inline_text(tbl_m1, variable = stage, level = "T3") resolves to "r inline_text(tbl_m1, variable = stage, level = "T3")".

The inline_text function has arguments for rounding the p-value (pvalue_fun) and the coefficients and confidence interval (estimate_fun). These default to the same rounding performed in the table, but can be modified when reporting inline.

For more details about inline code, review to the RStudio documentation page.

ddsjoberg/gtsummary documentation built on Nov. 3, 2023, 11:42 a.m.