gen_cor {CMHNPA}R Documentation

gen_cor Test

Description

gen_cor returns the generalised correlations and associated p-values together with tests of normality.

Usage

gen_cor(
  x,
  y,
  z = NULL,
  U,
  V,
  W = NULL,
  x_scores = NULL,
  y_scores = NULL,
  z_scores = NULL,
  n_perms = 0,
  perms_info = FALSE,
  rounding = 4
)

Arguments

x

a numeric vector or factor, commonly a response variable.

y

a numeric vector or factor, commonly a treatment variable.

z

an optional numeric vector or factor, commonly a block variable.

U

the maximum degree of correlation relating to the variable x.

V

the maximum degree of correlation relating to the variable y.

W

the maximum degree of correlation relating to the variable z. Required when z is included.

x_scores

optional scores related to the variable x.

y_scores

optional scores related to the variable y.

z_scores

optional scores related to the variable z.

n_perms

an optional numeric value indicating the number of permutations required.

perms_info

a TRUE of FALSE flag to indicate whether information regarding the progress on the number of permutations should be printed.

rounding

the number of decimal places the output should be rounded to. The default is 4.

Details

This function calculates up to three way generalised correlations. The function calculates three tests by default to test if the correlations are statistically significantly different from 0 with an option to run permuation testing.

Value

This function calculates the generalised correlations for up to three input variables.

References

Rayner, J.C.W and Livingston, G. C. (2022). An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA. Wiley.

Examples

attach(intelligence)
gen_cor(x = rank(score), y = age, U = 2, V = 2)

[Package CMHNPA version 1.1.1 Index]