Association measures and affine moments

VariationRatio: proportion of cases outside the modal category. YuleAssociation: Yule's Q and Y with standard errors and Wald intervals for a 2 by 2 table. TostCorrelation: two one-sided tests of correlation equivalence with Fisher's z. AffineMoments: mean and covariance of affine transformations of a random vector. Identical to the Python arm morie.fn.assocstats.

Usage

VariationRatio(x)

YuleAssociation(table, conf_level = 0.95)

TostCorrelation(r, n, low, high, alpha = 0.05)

AffineMoments(mean, cov, A, c = NULL, B = NULL, d = NULL)

Arguments

x

Observations of a nominal or ordinal variable.

table

A 2 by 2 table (matrix, rows a b / c d).

conf_level

Confidence level.

r

Sample correlation.

n

Sample size.

low, high

Equivalence bounds on the correlation.

alpha

Test level.

mean

Mean vector.

cov

Covariance matrix.

A, B

Transformation matrices.

c, d

Constant vectors.

Value

A number or a list.

References

Freeman, L. C. (1965). Elementary Applied Statistics. Wiley.

Yule, G. U. (1912). On the methods of measuring association between two attributes. Journal of the Royal Statistical Society 75, 579-652.

Lakens, D. (2017). Equivalence tests: a practical primer for t tests, correlations, and meta-analyses. Social Psychological and Personality Science 8, 355-362.

Examples

VariationRatio(c("a", "b", "a", "c", "a"))
#> [1] 0.4
YuleAssociation(matrix(c(20, 5, 10, 15), 2))$Q
#> [1] 0.7142857
TostCorrelation(0.02, 200, -0.2, 0.2)$p_value
#> [1] 0.005162714