plot_choices {specr}

Plot how analytical choices affect results

Description

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().

Usage

plot_choices(
  df,
  var = .data$estimate,
  group = NULL,
  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()).

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).

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"))