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().

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

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)

Value

a ggplot object.

Examples

# load additional library library(ggplot2) # for further customization of the plots
#> 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()