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()`

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plot_choices( df, var = .data$estimate, choices = c("x", "y", "model", "controls", "subsets"), desc = FALSE, null = 0 )

df | a data frame resulting from |
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var | which variable should be evaluated? Defaults to estimate (the effect sizes computed by |

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)