This functions plots how analytical choices affect the obtained results (i.e., the rank within the curve). Significant results are highlighted (negative = red, positive = blue, grey = nonsignificant). This functions creates the lower panel in plot_specs().

plot_choices(
  df,
  var = .data$estimate,
  choices = c("x", "y", "model", "controls", "subsets"),
  desc = FALSE,
  null = 0
)

Arguments

df

a data frame resulting from run_specs().

var

which variable should be evaluated? Defaults to estimate (the effect sizes computed by run_specs()).

choices

a vector specifying which analytical choices should be plotted. By default, all choices are plotted.

desc

logical value indicating whether the curve should the arranged in a descending order. Defaults to FALSE.

null

Indicate what value represents the 'null' hypothesis (Defaults to zero).

Value

a ggplot object.

Examples

# Run specification curve analysis results <- run_specs(df = example_data, y = c("y1", "y2"), x = c("x1", "x2"), model = c("lm"), controls = c("c1", "c2"), subsets = list(group1 = unique(example_data$group1), group2 = unique(example_data$group2))) # Plot simple table of choices plot_choices(results)
# Plot only specific choices plot_choices(results, choices = c("x", "y", "controls"))