Plot sample sizes

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 = "samplesizes". This function plots a histogram of sample sizes per specification. It can be added to the overall specification curve plot (see vignettes).

plot_samplesizes(df, var = .data$estimate, group = NULL, desc = FALSE)

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()).

group

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...)

desc

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

Value

a ggplot object.

Examples

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

# 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 ranked bar chart of sample sizes
plot_samplesizes(results)
#> Warning: `plot_samplesizes()` was deprecated in specr 1.0.0.
#> ℹ Please use `plot.specr.object()` instead.


# add a horizontal line for the median sample size
plot_samplesizes(results) +
  geom_hline(yintercept = median(results$fit_nobs),
             color = "darkgrey",
             linetype = "dashed") +
  theme_linedraw()