| plot_choices | R Documentation | 
This function is deprecated because the new version of specr uses a new analytic framework.
In this framework, you can plot a similar figure simply by using the generic 
plot() function.
and adding the argument type = "choices".
This functions plots how analytic 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$estimate,
  group = NULL,
  choices = c("x", "y", "model", "controls", "subsets"),
  desc = FALSE,
  null = 0
)
df | 
 a data frame resulting from   | 
var | 
 which variable should be evaluated? Defaults to estimate (the effect sizes computed by   | 
group | 
 Should the arrangement of the curve be grouped by a particular choice? Defaults to NULL, but can be any of the present choices (e.g., x, y, controls...)  | 
choices | 
 a vector specifying which analytical choices should be plotted. By default, all choices are plotted.  | 
desc | 
 logical value indicating whether the curve should the arranged in a descending order. Defaults to FALSE.  | 
null | 
 Indicate what value represents the 'null' hypothesis (Defaults to zero).  | 
a ggplot object.
# Run specification curve analysis
results <- run_specs(df = example_data,
                     y = c("y1", "y2"),
                     x = c("x1", "x2"),
                     model = c("lm"),
                     controls = c("c1", "c2"),
                     subsets = list(group1 = unique(example_data$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"))
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