Computes a z test for a difference of population Spearman correlations in a 2-group design. The test statistic uses a Bonett-Wright standard error for each Spearman correlation. The hypothesis testing results should be accompanied with a confidence interval for a difference in population Spearman correlation values.
test.spear2(cor1, cor2, n1, n2)
estimated Spearman correlation for group 1
estimated Spearman correlation for group 2
sample size for group 1
sample size for group 2
Returns a 1-row matrix. The columns are:
Estimate - estimate of correlation difference
z - z test statistic
p - two-sided p-value
Bonett DG, Wright TA (2000). “Sample size requirements for estimating Pearson, Kendall and Spearman correlations.” Psychometrika, 65(1), 23--28. ISSN 0033-3123, doi:10.1007/BF02294183 .
test.spear2(.684, .437, 100, 125)
#> Estimate z p
#> 0.247 2.498645 0.01246691
# Should return:
# Estimate z p
# 0.247 2.498645 0.01246691