diff_two_dep_cors {multid}

Difference between two dependent Pearson's correlations (with common index)

Description

Calculates Cohen's q effect size statistic for difference between two correlations, r_yx1 and r_yx2. Tests if Cohen's q is different from zero while accounting for dependency between the two correlations.

Usage

diff_two_dep_cors(data, y, x1, x2, level = 0.95, missing = "default")

Arguments

data

Data frame.

y

Character. Variable name of the common index variable.

x1

Character. Variable name.

x2

Character. Variable name.

level

Numeric. The confidence level required for the result output (Default .95)

missing

Character. Treatment of missing values (e.g., "ML", default = listwise deletion)

Value

Parameter estimates from the fitted structural path model.

Examples

set.seed(3864)
d<-data.frame(y=rnorm(100),x=rnorm(100))
d$x1<-d$x+rnorm(100)
d$x2<-d$x+rnorm(100)
diff_two_dep_cors(data=d,y="y",x1="x1",x2="x2")