Confidence interval for a 2-group correlation difference

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 for each correlation can be obtained using ci.fisher.

For more details, see Section 2.17 of Bonett (2021, Volume 2)

Usage

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 .

Bonett DG (2021). Statistical Methods for Psychologists https://dgbonett.sites.ucsc.edu/.

Examples

ci.cor2.gen(.64, .55, .71, .31, .18, .43)
#>  Estimate   LL     UL
#>      0.33 0.18 0.4776

# Should return:
# Estimate    LL     UL
#      0.33 0.18 0.4776