ci.cor2.gen {statpsych} | R Documentation |
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 function requires 100(1 - alpha)% confidence intervals for each correlation as input. This function also can be used to compute a confidence interval for the difference of two Cronbach reliability coefficients.
ci.cor2.gen(cor1, ll1, ul1, cor2, ll2, ul2)
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 |
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
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.
ci.cor2.gen(.4, .35, .47, .2, .1, .32) # Should return: # Estimate LL UL # [1,] 0.2 0.07 0.3220656