CC: Compute congruence coefficient

In SimDesign: Structure for Organizing Monte Carlo Simulation Designs

Compute congruence coefficient

Description

Computes the congruence coefficient, also known as an "unadjusted" correlation or Tucker's congruence coefficient.

Usage

CC(x, y = NULL, unname = FALSE)

Arguments

x	a vector or data.frame/matrix containing the variables to use. If a vector then the input y is required, otherwise the congruence coefficient is computed for all bivariate combinations
y	(optional) the second vector input to use if x is a vector
unname	logical; apply unname to the results to remove any variable names?

Author(s)

Phil Chalmers [e-mail]

References

Chalmers, R. P., & Adkins, M. C. (2020). Writing Effective and Reliable Monte Carlo Simulations with the SimDesign Package. The Quantitative Methods for Psychology, 16(4), 248-280. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.20982/tqmp.16.4.p248")}

Sigal, M. J., & Chalmers, R. P. (2016). Play it again: Teaching statistics with Monte Carlo simulation. Journal of Statistics Education, 24(3), 136-156. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10691898.2016.1246953")}

See Also

cor

Examples

vec1 <- runif(1000)
vec2 <- runif(1000)

CC(vec1, vec2)
# compare to cor()
cor(vec1, vec2)

# column input
df <- data.frame(vec1, vec2, vec3 = runif(1000))
CC(df)
cor(df)

SimDesign documentation built on Sept. 11, 2024, 8 p.m.