ASMR Excess vs Confounders Correlation [World]

.chart_world_easmr_correl.r

library(readr)
library(GGally)

sf <- 2
width <- 900 * sf
height <- 450 * sf

options(vsc.dev.args = list(width = width, height = height, res = 72 * sf))

source(paste0(
  "https://gist.githubusercontent.com/USMortality/",
  "cf0dc23d0d5ca609539fe11c9c089fcc/raw/asmr_country_dataset.r"
))

# Analysis
df2 <- df |>
  filter(date == 2020) |>
  select(
    -iso3c,
    -date,
    -total_vaccinations_per_hundred,
    -people_vaccinated_per_hundred,
    -people_fully_vaccinated_per_hundred,
    -total_boosters_per_hundred,
  )

chart <- GGally::ggcorr(df2, geom = "blank", label = TRUE, hjust = 1) +
  geom_point(
    size = 10, aes(color = coefficient < 0, alpha = abs(coefficient) >= 0.4)
  ) +
  scale_alpha_manual(values = c("TRUE" = 0.25, "FALSE" = 0)) +
  guides(color = FALSE, alpha = FALSE) +
  ggplot2::coord_cartesian(clip = "off") +
  ggplot2::theme(plot.margin = ggplot2::unit(c(1, 0, 0, 2.5), "cm")) +
  labs(title = "Correlation Matrix [2020]")

ggplot2::ggsave(
  filename = "chart1.png", plot = chart, width = width, height = height,
  units = "px", dpi = 72 * sf, device = grDevices::png, type = c("cairo")
)


# By Date
cor_by_date <- function(df) {
  df |>
    group_by(date) |>
    summarize(
      across(everything(), ~ cor(.x, asmr_who_ex_p,
        use = "pairwise.complete.obs"
      ))
    ) |>
    tidyr::pivot_longer(
      cols = -date, names_to = "variable", values_to = "correlation"
    ) |>
    filter(variable != "asmr_who_ex_p") # Exclude self-correlation
}

# Create correlation bins
cor_results <- cor_by_date(df |> select(-iso3c)) |>
  mutate(correlation_group = cut(
    correlation,
    breaks = c(-Inf, -0.4, 0.4, Inf),
    labels = c("< -0.4", "-0.4 to 0.4", "> 0.4"),
    include.lowest = TRUE
  ))

# Plot the heatmap with the simplified grouped correlation and values
chart <- ggplot(cor_results, aes(x = date, y = variable, fill = correlation_group)) +
  geom_tile() +
  geom_text(
    aes(label = sprintf("%.1f", correlation)),
    size = 3, color = "black"
  ) +
  scale_fill_manual(values = c(
    "< -0.4" = "#1a9850",
    "-0.4 to 0.4" = "white",
    "> 0.4" = "#d73027"
  )) +
  theme_minimal() +
  labs(
    title = "Correlation of eASMR with other variables",
    fill = "Correlation"
  )

ggplot2::ggsave(
  filename = "chart2.png", plot = chart, width = width, height = height,
  units = "px", dpi = 72 * sf, device = grDevices::png, type = c("cairo")
)

https://www.mortality.watch/charts/list.html#asmr-excess-vs-confounders-correlation-world