This function plots the a ranked specification curve. Confidence intervals can be included. Significant results are highlighted (negative = red, positive = blue, grey = nonsignificant). This functions creates the upper panel in `plot_specs()`

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plot_curve( df, var = .data$estimate, desc = FALSE, ci = TRUE, ribbon = FALSE, legend = 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 |

desc | logical value indicating whether the curve should the arranged in a descending order. Defaults to FALSE. |

ci | logical value indicating whether confidence intervals should be plotted. |

ribbon | logical value indicating whether a ribbon instead should be plotted. |

legend | logical value indicating whether the legend should be plotted Defaults to FALSE. |

null | Indicate what value represents the null hypothesis (Defaults to zero) |

a ggplot object.

#> Warning: package ‘ggplot2’ was built under R version 3.6.2# 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 specification curve plot_curve(results)# Ribbon instead of CIs and customize further plot_curve(results, ci = FALSE, ribbon = TRUE) + geom_hline(yintercept = 0) + geom_hline(yintercept = median(results$estimate), linetype = "dashed") + theme_linedraw()