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$estimate,
group = NULL,
choices = c("x", "y", "model", "controls", "subsets"),
desc = FALSE,
null = 0
)
a data frame resulting from run_specs()
.
which variable should be evaluated? Defaults to estimate (the effect sizes computed by run_specs()
).
Should the arrangement of the curve be grouped by a particular choice? Defaults to NULL, but can be any of the present choices (e.g., x, y, controls...)
a vector specifying which analytical choices should be plotted. By default, all choices are plotted.
logical value indicating whether the curve should the arranged in a descending order. Defaults to FALSE.
Indicate what value represents the 'null' hypothesis (Defaults to zero).
a ggplot object.
# Run specification curve analysis
results <- run_specs(df = example_data,
y = c("y1", "y2"),
x = c("x1", "x2"),
model = c("lm"),
controls = c("c1", "c2"),
subsets = list(group1 = unique(example_data$group1),
group2 = unique(example_data$group2)))
# Plot simple table of choices
plot_choices(results)
#> Warning: `plot_choices()` was deprecated in specr 1.0.0.
#> ℹ Please use `plot.specr.object()` instead.
# Plot only specific choices
plot_choices(results,
choices = c("x", "y", "controls"))