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
)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 toNULLto omit the confidence interval.- digits
Number of decimal places used when printing the result (default
3).
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.
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.
Examples
tab <- table(sochealth$smoking, sochealth$education)
assoc_measures(tab)
#> Measure Estimate SE CI lower CI upper p
#> Cramer's V 0.136 -- 0.079 0.191 < 0.001
#> Contingency Coefficient 0.134 -- -- -- < 0.001
#> Lambda symmetric 0.000 0.000 0.000 0.000 --
#> Lambda R|C 0.000 0.000 0.000 0.000 --
#> Lambda C|R 0.000 0.000 0.000 0.000 --
#> Goodman-Kruskal's Tau R|C 0.018 0.008 0.003 0.034 0.023
#> Goodman-Kruskal's Tau C|R 0.008 0.003 0.001 0.014 0.022
#> Uncertainty Coefficient symmetric 0.011 0.005 0.002 0.021 0.021
#> Uncertainty Coefficient R|C 0.018 0.008 0.003 0.032 0.021
#> Uncertainty Coefficient C|R 0.009 0.004 0.001 0.016 0.021
#> Goodman-Kruskal Gamma -0.268 0.056 -0.378 -0.158 < 0.001
#> Kendall's Tau-b -0.126 0.027 -0.180 -0.073 < 0.001
#> Kendall's Tau-c -0.117 0.026 -0.167 -0.067 < 0.001
#> Somers' D R|C -0.091 0.020 -0.131 -0.052 < 0.001
#> Somers' D C|R -0.175 0.038 -0.249 -0.101 < 0.001
assoc_measures(tab, type = "nominal")
#> Measure Estimate SE CI lower CI upper p
#> Cramer's V 0.136 -- 0.079 0.191 < 0.001
#> Contingency Coefficient 0.134 -- -- -- < 0.001
#> Lambda symmetric 0.000 0.000 0.000 0.000 --
#> Lambda R|C 0.000 0.000 0.000 0.000 --
#> Lambda C|R 0.000 0.000 0.000 0.000 --
#> Goodman-Kruskal's Tau R|C 0.018 0.008 0.003 0.034 0.023
#> Goodman-Kruskal's Tau C|R 0.008 0.003 0.001 0.014 0.022
#> Uncertainty Coefficient symmetric 0.011 0.005 0.002 0.021 0.021
#> Uncertainty Coefficient R|C 0.018 0.008 0.003 0.032 0.021
#> Uncertainty Coefficient C|R 0.009 0.004 0.001 0.016 0.021
assoc_measures(tab, type = "ordinal")
#> Measure Estimate SE CI lower CI upper p
#> Goodman-Kruskal Gamma -0.268 0.056 -0.378 -0.158 < 0.001
#> Kendall's Tau-b -0.126 0.027 -0.180 -0.073 < 0.001
#> Kendall's Tau-c -0.117 0.026 -0.167 -0.067 < 0.001
#> Somers' D R|C -0.091 0.020 -0.131 -0.052 < 0.001
#> Somers' D C|R -0.175 0.038 -0.249 -0.101 < 0.001