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
)
```

- 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).

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"))
```