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Render a Forest Plot Table from Disproportionality Data

Source: R/disproportionality_analysis.R
render_forest_table.Rd

This function takes a data frame containing disproportionality analysis results and generates a forest plot table using the forestplot package. It highlights results with lower confidence intervals greater than zero in red.

Usage

render_forest_table(disproportionality_df)

Arguments

disproportionality_df

A data.table containing the following columns:

  • nested: Type of analysis (e.g., "Crude", "Adjusted")

  • D_E: Observed count

  • expected: Expected count

  • IC_median: Median Information Component

  • IC_lower: Lower bound of the 95% confidence interval

  • IC_upper: Upper bound of the 95% confidence interval

Value

A forestplot object representing the forest plot table.

Details

The function:

  • Formats the input data for display

  • Highlights rows with significant IC values (lower CI > 0) in red

  • Adds horizontal lines and zebra striping for readability

  • Sets custom x-axis ticks and labels

Examples

if (FALSE) { # \dontrun{
library(data.table)
df <- data.table(
  nested = c("Crude", "Adjusted"),
  D_E = c(10, 8),
  expected = c(5.5, 6.2),
  IC_median = c(1.2, 0.8),
  IC_lower = c(0.5, -0.2),
  IC_upper = c(1.9, 1.3)
)
render_forest_table(df)
} # }