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Calculate Corrected Covered Area (CCA) and Generate a Heatmap

cca_heatmap.Rd

This function calculates the Corrected Covered Area (CCA) for a set of studies across systematic reviews and generates a heatmap of study inclusion.

Usage

cca_heatmap(data, show_plot = TRUE)

Arguments

data

A tibble or dataframe with columns:

  • study (character): Study identifiers.

  • review (character): Review identifiers.

  • status (character): Study status, one of c("included", "excluded", "ineligible", NA).

show_plot

Logical; if TRUE, returns a heatmap plot, otherwise only the CCA value.

Value

A list with:

  • CCA (numeric): The Corrected Covered Area value.

  • plot (ggplot object): The heatmap (if show_plot = TRUE).

References

Pieper, D., Antoine, S. L., Mathes, T., Neugebauer, E. A., & Eikermann, M. (2014). Systematic review finds overlapping reviews were not mentioned in every other overview. Journal of Clinical Epidemiology, 67(4), 368–375. doi:10.1016/j.jclinepi.2013.11.007

Hedges, L. V., & Olkin, I. (1988). Statistical Methods for Meta-Analysis. Academic Press.

Examples

library(tidyverse)
#> ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
#> ✔ dplyr     1.1.4     ✔ readr     2.1.5
#> ✔ forcats   1.0.0     ✔ stringr   1.5.1
#> ✔ ggplot2   3.5.2     ✔ tibble    3.2.1
#> ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
#> ✔ purrr     1.0.4     
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()
#> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(junoR)
# Example dataset
data <- tibble(
  study = rep(paste0("Study_", 1:5), times = 5),
  review = rep(paste0("Review_", 1:5), each = 5),
  status = c("included", "included", "ineligible", NA, NA,
             NA, "included", NA, "excluded", NA,
             "included", NA, "included", "excluded", "ineligible",
             "included", "excluded", "included", "excluded", NA,
             NA, "included", "ineligible", NA, "excluded")
)

# Run function
result <- cca_heatmap(data)
print(result$CCA)
#> [1] 41.66667
print(result$plot)