spicy (version 0.6.0)

assoc_measures: Association measures summary table

Description

assoc_measures() computes a range of association measures for a two-way contingency table and returns them in a tidy data frame.

Usage

assoc_measures(
  x,
  type = c("all", "nominal", "ordinal"),
  conf_level = 0.95,
  digits = 3L
)

Value

A data frame with columns measure, estimate, se, ci_lower, ci_upper, and p_value. For nominal measures (Cramer's V, Phi, Contingency Coef.), the p-value comes from the Pearson chi-squared test of independence. For all other measures, it is a Wald z-test of H0: measure = 0.

Arguments

x

A contingency table (of class table).

type

Which family of measures to compute: "all" (default), "nominal", or "ordinal".

conf_level

A number between 0 and 1 giving the confidence level (default 0.95). Set to NULL to omit the confidence interval.

digits

Number of decimal places used when printing the result (default 3).

Details

type = "all" (the default) returns all nominal and ordinal measures. Use type = "nominal" or type = "ordinal" to restrict the output to a single family.

The nominal family includes cramer_v(), contingency_coef(), lambda_gk(), goodman_kruskal_tau(), uncertainty_coef(), and (for 2x2 tables) phi() and yule_q().

The ordinal family includes gamma_gk(), kendall_tau_b(), kendall_tau_c(), and somers_d().

Standard error formulas follow the DescTools implementations (Signorell et al., 2024).

References

Agresti, A. (2002). Categorical Data Analysis (2nd ed.). Wiley.

Liebetrau, A. M. (1983). Measures of Association. Sage.

Signorell, A. et al. (2024). DescTools: Tools for Descriptive Statistics. R package.

See Also

cramer_v(), gamma_gk(), kendall_tau_b()

Examples

tab <- table(sochealth$smoking, sochealth$education)
assoc_measures(tab)
assoc_measures(tab, type = "nominal")
assoc_measures(tab, type = "ordinal")