Skip to contents

Plot design-check p-values against the uniform reference

Source: R/check_pvalues.R
plot_check_pvalues.Rd

Histogram of test p-values with a dotted line at the Uniform(0, 1) expectation and a dashed line at alpha. A flat histogram sitting on the reference line, with roughly alpha of the mass below the dashed line, is direct evidence that the analyzed sample is sound.

Usage

plot_check_pvalues(
  x,
  p_col = "p_value",
  group = NULL,
  alpha = 0.05,
  binwidth = 0.05,
  fdr = FALSE,
  xlab = "p-value"
)

Arguments

x

A data frame of test results, typically one element of the list returned by stack_checks.

p_col

Character scalar naming the p-value column (default "p_value").

group

Optional character scalar naming a column to adjust within. When supplied, the FDR adjustment is applied separately within each level of that column (e.g. group = "study_id" for a within-study adjustment); the returned summary is still a single row across all tests. When NULL (default) the adjustment is applied across all tests at once. The two answer different questions, so the choice belongs at the call site.

alpha

Rejection threshold (default 0.05).

binwidth

Histogram bin width (default 0.05, giving 20 bins).

fdr

Logical. When TRUE, the plot is faceted into unadjusted and Benjamini-Hochberg-adjusted panels (default FALSE).

xlab

Axis label for the p-value axis.

Value

A ggplot object. Deliberately unthemed beyond theme_minimal() so that a project theme can be added to it.

See also

Other across-study summaries: report_checks(), stack_checks(), summarize_check_pvalues()

Examples

set.seed(1)
tests <- data.frame(study_id = rep(letters[1:5], each = 20),
                    p_value = runif(100))
plot_check_pvalues(tests)
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_bar()`).

plot_check_pvalues(tests, group = "study_id", fdr = TRUE)
#> Warning: Removed 4 rows containing missing values or values outside the scale range
#> (`geom_bar()`).