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Plot Hierarchical CFR Model Results

Source: R/plot_CFR_hierarchical.R
plot_CFR_hierarchical.Rd

Creates professional visualizations of the hierarchical GAM CFR model results including observed data points and modeled time series predictions. Generates an 8.5x11 inch PDF with faceted plots showing country-specific CFR trends over time.

Usage

plot_CFR_hierarchical(
  PATHS,
  countries_to_plot = NULL,
  pdf_width = 8.5,
  pdf_height = 11,
  ncol_facet = 4,
  show_ci = TRUE,
  verbose = TRUE
)

Arguments

PATHS

List containing paths to data directories, typically from get_paths()

countries_to_plot

Character vector of ISO codes to plot. If NULL, plots top 20 countries by data availability

pdf_width

Numeric, width of PDF in inches (default 8.5)

pdf_height

Numeric, height of PDF in inches (default 11)

ncol_facet

Integer, number of columns for facet wrap (default 4)

show_ci

Logical, whether to show confidence intervals (default TRUE)

verbose

Logical, whether to print progress messages (default TRUE)

Value

Invisibly returns a list of ggplot objects. Saves PDF to DOCS_FIGURES directory.

Details

The function creates a multi-page PDF containing:

  • Page 1: Overview plot with temporal trend and data summary

  • Following pages: Faceted plots of country-specific CFR trends

  • Each panel shows observed CFR (points) and model predictions (lines with 95% predictive intervals for one year's CFR)

  • Years after a country's last fitted year (is_forecast) are drawn dashed on a shaded background: the model holds each trend at its last fitted year there

  • A page of each country's deviation from the population trend (the model's country intercept is weakly identified, so the deviation is taken from the fitted country curve)

Examples

if (FALSE) { # \dontrun{
PATHS <- get_paths()
# First run the model
est_CFR_hierarchical(PATHS)
# Then create plots
plot_CFR_hierarchical(PATHS)

# Plot specific countries
plot_CFR_hierarchical(PATHS, 
  countries_to_plot = c("COD", "NGA", "KEN", "MOZ", "ETH", "ZWE"))
} # }