p: Vector of expected values. See stats::chisq.test().
nrow, ncol: The number of rows/columns in the contingency table.
Examples
library(effectsize)## 2D tables## ---------data("Music_preferences2")Music_preferences2
cramers_v(Music_preferences2, adjust =FALSE)v_to_t(0.80,3,4)tschuprows_t(Music_preferences2)## Goodness of fit## ---------------data("Smoking_FASD")Smoking_FASD
cohens_w(Smoking_FASD, p = c(0.015,0.010,0.975))w_to_fei(0.11, p = c(0.015,0.010,0.975))fei(Smoking_FASD, p = c(0.015,0.010,0.975))## Power analysis## --------------# See https://osf.io/cg64s/p0 <- c(0.35,0.65)Fei <-0.3pwr::pwr.chisq.test( w = fei_to_w(Fei, p = p0), df = length(p0)-1, sig.level =0.01, power =0.85)
References
Ben-Shachar, M.S., Patil, I., Thériault, R., Wiernik, B.M., Lüdecke, D. (2023). Phi, Fei, Fo, Fum: Effect Sizes for Categorical Data That Use the Chi‑Squared Statistic. Mathematics, 11, 1982. tools:::Rd_expr_doi("10.3390/math11091982")
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). New York: Routledge.
See Also
cramers_v()chisq_to_fei()
Other convert between effect sizes: d_to_r(), diff_to_cles, eta2_to_f2(), odds_to_probs(), oddsratio_to_riskratio()