weat_resampling: Test of significance for WEAT

In sweater: Speedy Word Embedding Association Test and Extras Using R

Test of significance for WEAT

Description

This function conducts the test of significance for WEAT as described in Caliskan et al. (2017). The exact test (proposed in Caliskan et al.) takes an unreasonably long time, if the total number of words in S and T is larger than 10. The resampling test is an approximation of the exact test.

Usage

weat_exact(x)

weat_resampling(x, n_resampling = 9999)

Arguments

x	an object from the weat function.
n_resampling	an integer specifying the number of replicates used to estimate the exact test

Value

A list with class "htest"

References

Caliskan, A., Bryson, J. J., & Narayanan, A. (2017). Semantics derived automatically from language corpora contain human-like biases. Science, 356(6334), 183-186. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1126/science.aal4230")}

Examples

# Reproduce the number in Caliskan et al. (2017) - Table 1, "Math vs. Arts"
data(glove_math)
S1 <- c("math", "algebra", "geometry", "calculus", "equations",
"computation", "numbers", "addition")
T1 <- c("poetry", "art", "dance", "literature", "novel", "symphony", "drama", "sculpture")
A1 <- c("male", "man", "boy", "brother", "he", "him", "his", "son")
B1 <- c("female", "woman", "girl", "sister", "she", "her", "hers", "daughter")
sw <- weat(glove_math, S1, T1, A1, B1)
weat_resampling(sw)

sweater documentation built on Nov. 7, 2023, 5:08 p.m.