calculate_clusters_pvalues {jlmerclusterperm}

Calculate bootstrapped p-values of cluster-mass statistics

Description

Calculate bootstrapped p-values of cluster-mass statistics

Usage

calculate_clusters_pvalues(
  empirical_clusters,
  null_cluster_dists,
  add1 = FALSE
)

clusters_are_comparable(empirical_clusters, null_cluster_dists, error = FALSE)

Arguments

empirical_clusters

A empirical_clusters object

null_cluster_dists

A null_cluster_dists object

add1

Whether to add 1 to the numerator and denominator when calculating the p-value. Use TRUE to effectively count the observed statistic as part of the permuted null distribution (recommended with larger nsim prior to publishing results).

error

Whether to throw an error if incompatible

Value

An empirical_clusters object augmented with p-values.

See Also

extract_empirical_clusters(), extract_null_cluster_dists()

Examples

library(dplyr, warn.conflicts = FALSE)

# Specification object
spec <- make_jlmer_spec(
  weight ~ 1 + Diet, filter(ChickWeight, Time <= 20),
  subject = "Chick", time = "Time"
)
spec

# Make empirical clusters
empirical_statistics <- compute_timewise_statistics(spec)
empirical_clusters <- extract_empirical_clusters(empirical_statistics, threshold = 2)
empirical_clusters

# Make null cluster-mass distribution
reset_rng_state()
null_statistics <- permute_timewise_statistics(spec, nsim = 100)
null_cluster_dists <- extract_null_cluster_dists(null_statistics, threshold = 2)

# Significance test the empirical cluster(s) from each predictor against the simulated null
calculate_clusters_pvalues(empirical_clusters, null_cluster_dists)

# Set `add1 = TRUE` to normalize by adding 1 to numerator and denominator
calculate_clusters_pvalues(empirical_clusters, null_cluster_dists, add1 = TRUE)

# This sequence of procedures is equivalent to `clusterpermute()`
reset_rng_state()
clusterpermute(spec, threshold = 2, nsim = 100, progress = FALSE)

# The empirical clusters and the null cluster-mass distribution must be comparable
empirical_clusters2 <- extract_empirical_clusters(empirical_statistics, threshold = 3)
# For example, below code errors because thresholds are different (2 vs. 3)
try( calculate_clusters_pvalues(empirical_clusters2, null_cluster_dists) )

# Check for compatibility with `clusters_are_comparable()`
clusters_are_comparable(empirical_clusters, null_cluster_dists)
clusters_are_comparable(empirical_clusters2, null_cluster_dists)