R/plot.check_overdisp.R

In see: Model Visualisation Toolbox for 'easystats' and 'ggplot2'

#' @export
plot.see_check_overdisp <- function(
  x,
  linewidth = 0.8,
  size_title = 12,
  size_axis_title = base_size,
  base_size = 10,
  theme = NULL,
  colors = c("#3aaf85", "#1b6ca8"),
  type = 1,
  ...
) {
  .plot_diag_overdispersion(
    x,
    theme = theme,
    colors = colors,
    linewidth = linewidth,
    size_title = size_title,
    size_axis_title = size_axis_title,
    base_size = base_size,
    type = type
  )
}


.plot_diag_overdispersion <- function(
  x,
  theme = NULL,
  size_axis_title = base_size,
  size_title = 12,
  base_size = 10,
  colors = c("#3aaf85", "#1b6ca8"),
  linewidth = 0.8,
  type = 1,
  ...
) {
  theme <- .set_default_theme(
    x,
    theme,
    base_size,
    size_axis_title,
    size_title,
    default_theme = ggplot2::theme_grey()
  )

  if (is.null(type) || type == 1) {
    p <- ggplot2::ggplot(x) +
      ggplot2::aes(x = .data$Predicted) +
      ggplot2::geom_smooth(
        ggplot2::aes(y = .data$V),
        linewidth = linewidth,
        color = colors[2],
        se = FALSE
      ) +
      ggplot2::geom_smooth(
        ggplot2::aes(y = .data$Res2),
        linewidth = linewidth,
        color = colors[1]
      ) +
      ggplot2::labs(
        title = "Misspecified dispersion and zero-inflation",
        subtitle = "Observed residual variance (green) should follow predicted residual variance (blue)",
        x = "Predicted mean",
        y = "Residual variance"
      ) +
      theme
  } else {
    p <- ggplot2::ggplot(x) +
      ggplot2::aes(x = .data$Predicted) +
      ggplot2::geom_point(ggplot2::aes(y = .data$StdRes)) +
      ggplot2::geom_hline(
        yintercept = c(-2, 2, -4, 4),
        linetype = c("solid", "solid", "dashed", "dashed"),
        color = c(rep(colors[1], 2), rep(colors[2], 2))
      ) +
      ggplot2::labs(
        title = "Misspecified dispersion and zero-inflation",
        subtitle = "Most points should be within solid lines, few points outside dashed lines",
        x = "Predicted mean",
        y = "Standardized resiuduals"
      ) +
      theme
  }

  p
}