Bootstrap Distribution of Effective Size — esize_boot

Computes a bootstrap distribution for effective size using either Tredoux's E' or Malpass's adjusted E.

Usage

esize_boot_dist(
  lineup_input,
  k,
  metric = c("tredoux", "malpass"),
  input_type = c("vector", "table"),
  R = 1000,
  unbiased = FALSE
)

Arguments

lineup_input: A numeric lineup vector or a lineup table.
k: Nominal lineup size (suspect + fillers).
metric: Either "tredoux" or "malpass".
input_type: Either "vector" or "table".
R: Number of bootstrap resamples.
unbiased: Logical. For metric = "tredoux", bootstrap the small-sample corrected E' of esize_T(unbiased = TRUE) instead of the plug-in estimate. Default FALSE.

Value

A numeric vector of bootstrap estimates, carrying an "n" attribute equal to the number of lineup choices resampled. With unbiased = TRUE, resamples in which every choice fell on a different member have an unbounded corrected estimate; they are retained as Inf, with a warning, and their number is recorded in an "n_undefined" attribute.

Details

Percentile or BCa intervals from the plug-in E' bootstrap are not valid tests of exact uniform fairness. The population maximum E'=k is a nonregular boundary. If the sample size is not a multiple of k, even the largest attainable empirical E' is below k, so those intervals have zero coverage at exact fairness. More bootstrap replicates cannot fix this.

Examples

vec <- round(runif(200, 1, 6))
dist <- esize_boot_dist(vec, k = 6, metric = "tredoux", R = 500)
dist_corrected <- esize_boot_dist(vec, k = 6, R = 500, unbiased = TRUE)