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_choices( df, var = .data$estimate, choices = c("x", "y", "model", "controls", "subsets"), desc = FALSE, null = 0 )
a data frame resulting from
which variable should be evaluated? Defaults to estimate (the effect sizes computed by
a vector specifying which analytical choices should be plotted. By default, all choices are plotted.
logical value indicating whether the curve should the arranged in a descending order. Defaults to FALSE.
Indicate what value represents the 'null' hypothesis (Defaults to zero).
a ggplot object.
# Run specification curve analysis results <- run_specs(df = example_data, y = c("y1", "y2"), x = c("x1", "x2"), model = c("lm"), controls = c("c1", "c2"), subsets = list(group1 = unique(example_data$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"))