Confidence interval for a 2-group correlation difference

Source: R/statpsych2.R

Computes a 100(1 - alpha)% confidence interval for a difference in population correlations in a 2-group design. The correlations can be Pearson, Spearman, partial, semipartial, or point-biserial correlations. The correlations could also be correlations between two latent factors. The function requires a point estimate and a 100(1 - alpha)% confidence interval for each correlation as input. The confidence intervals can be obtained using the ci.fisher function.

ci.cor2.gen(cor1, ll1, ul1, cor2, ll2, ul2)

Arguments

cor1

estimated correlation for group 1

ll1

lower limit for group 1 correlation

ul1

upper limit for group 1 correlation

cor2

estimated correlation for group 2

ll2

lower limit for group 2 correlation

ul2

upper limit for group 2 correlation

Value

Returns a 1-row matrix. The columns are:

  • Estimate - estimated correlation difference

  • LL - lower limit of the confidence interval

  • UL - upper limit of the confidence interval

References

Zou GY (2007). “Toward using confidence intervals to compare correlations.” Psychological Methods, 12(4), 399--413. ISSN 1939-1463, doi:10.1037/1082-989X.12.4.399 .

Examples

ci.cor2.gen(.4, .35, .47, .2, .1, .32)
#>  Estimate   LL        UL
#>       0.2 0.07 0.3220656

# Should return:
# Estimate   LL        UL
#      0.2 0.07 0.3220656