Confidence interval for a difference in dependent Pearson correlations

Source: R/statpsych2.R

Computes a confidence interval for a difference in population Pearson correlations that are estimated from the same sample and have one variable in common. A bias adjustment is used to reduce the bias of each Fisher transformed correlation. An approximate standard error is recovered from the confidence interval.

ci.cor.dep(alpha, cor1, cor2, cor12, n)

Arguments

alpha

alpha level for 1-alpha confidence

cor1

estimated Pearson correlation between y and x1

cor2

estimated Pearson correlation between y and x2

cor12

estimated Pearson correlation between x1 and x2

n

sample size

Value

Returns a 1-row matrix. The columns are:

  • Estimate - estimated correlation difference

  • SE - recovered standard error

  • 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.cor.dep(.05, .396, .179, .088, 166)
#>  Estimate        SE         LL       UL
#>     0.217 0.1026986 0.01323072 0.415802

# Should return:
# Estimate        SE         LL       UL
#    0.217 0.1026986 0.01323072 0.415802