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CC

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 cogruence 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)

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. 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. doi: 10.1080/10691898.2016.1246953

See Also

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

Structure for Organizing Monte Carlo Simulation Designs

v2.3
GPL (>= 2)
Authors
Phil Chalmers [aut, cre] (<https://orcid.org/0000-0001-5332-2810>), Matthew Sigal [ctb], Ogreden Oguzhan [ctb]
Initial release

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