kendall_tau_c() computes Stuart's Tau-c (also known as
Kendall's Tau-c) for a two-way contingency table of ordinal
variables.
kendall_tau_c(
x,
detail = FALSE,
conf_level = 0.95,
digits = 3L,
.include_se = FALSE
)Same structure as cramer_v(): a scalar when
detail = FALSE, a named vector when detail = TRUE.
The p-value tests H0: tau-c = 0 (Wald z-test).
A contingency table (of class table).
Logical. If FALSE (default), return the estimate
as a numeric scalar. If TRUE, return a named numeric vector
including confidence interval and p-value.
A number between 0 and 1 giving the confidence
level (default 0.95). Only used when detail = TRUE. Set
to NULL to omit the confidence interval.
Number of decimal places used when printing the
result (default 3). Only affects the detail = TRUE output.
Internal parameter; do not use.
Stuart's Tau-c is computed as
\(\tau_c = 2m(C - D) / (n^2(m - 1))\), where
\(m = \min(r, c)\). It is appropriate for rectangular
tables and is not restricted to the range \([-1, 1]\) only for
square tables.
Standard error formulas follow the DescTools implementations
(Signorell et al., 2024); see cramer_v() for full references.
kendall_tau_b(), gamma_gk(), somers_d(),
assoc_measures()
Other association measures:
assoc_measures(),
contingency_coef(),
cramer_v(),
gamma_gk(),
goodman_kruskal_tau(),
kendall_tau_b(),
lambda_gk(),
phi(),
somers_d(),
uncertainty_coef(),
yule_q()
tab <- table(sochealth$education, sochealth$self_rated_health)
kendall_tau_c(tab)
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