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Transform text from report::report() into LaTeX-friendly output.

Source: R/reporting.R
latexify_report.Rd

This function transforms the text output from report::report() by performing several substitutions to prepare the text for LaTeX typesetting. In particular, it replaces instances of R2, %, and ~ with the corresponding LaTeX code. Additionally, it provides options to:

  • Omit bullet items marked as "non-significant" (when only_sig = TRUE).

  • Remove a concluding note about standardized parameters (when remove_std = TRUE).

  • Wrap bullet items in a LaTeX itemize environment or leave them as plain text (controlled by itemize).

Usage

latexify_report(
  x,
  print_result = TRUE,
  only_sig = FALSE,
  remove_std = FALSE,
  itemize = TRUE
)

Arguments

x

Character vector or a single string containing the report text.

print_result

Logical. If TRUE (default), the formatted text is printed to the console.

only_sig

Logical. If TRUE, bullet items containing "non-significant" are omitted. Default is FALSE.

remove_std

Logical. If TRUE, the final standardized parameters note is removed. Default is FALSE.

itemize

Logical. If TRUE (default), bullet items are wrapped in a LaTeX itemize environment; otherwise the bullet markers are simply removed.

Value

A single string with the LaTeX-friendly formatted report text.

Examples

# \donttest{
if (requireNamespace("report", quietly = TRUE)) {
  # Simple linear model on the iris dataset
  model <- stats::lm(
    Sepal.Length ~ Sepal.Width + Petal.Length,
    data = datasets::iris
  )

  # Format the report output, showing only significant items, removing the
  # standard note, and wrapping bullet items in an itemize environment.
  report_text <- try(report::report(model), silent = TRUE)
  if (!inherits(report_text, "try-error")) {
    latexify_report(
      report_text,
      only_sig = TRUE,
      remove_std = TRUE,
      itemize = TRUE
    )
  }
}
#> We fitted a linear model (estimated using OLS) to predict Sepal.Length with Sepal.Width and Petal.Length (formula: Sepal.Length $\sim$ Sepal.Width + Petal.Length). The model explains a statistically significant and substantial proportion of variance ($R^2$ = 0.84, F(2, 147) = 386.39, p < .001, adj. $R^2$ = 0.84). The model's intercept, corresponding to Sepal.Width = 0 and Petal.Length = 0, is at 2.25 (95\% CI [1.76, 2.74], t(147) = 9.07, p < .001). Within this model:
#> 
#> \begin{itemize}
#> \item The effect of Sepal Width is statistically significant and positive (beta = 0.60, 95\% CI [0.46, 0.73], t(147) = 8.59, p < .001; Std. beta = 0.31, 95\% CI [0.24, 0.39])
#> \item The effect of Petal Length is statistically significant and positive (beta = 0.47, 95\% CI [0.44, 0.51], t(147) = 27.57, p < .001; Std. beta = 1.01, 95\% CI [0.93, 1.08])
#> \end{itemize}
#> 
# }