View source: R/convert_between_xtabcorr.R
w_to_fei | R Documentation |
Enables a conversion between different indices of effect size, such as Cohen's w to פ (Fei), and Cramer's V to Tschuprow's T.
w_to_fei(w, p)
w_to_v(w, nrow, ncol)
w_to_t(w, nrow, ncol)
w_to_c(w)
fei_to_w(fei, p)
v_to_w(v, nrow, ncol)
t_to_w(t, nrow, ncol)
c_to_w(c)
v_to_t(v, nrow, ncol)
t_to_v(t, nrow, ncol)
w , c , v , t , fei |
Effect size to be converted |
p |
Vector of expected values. See |
nrow , ncol |
The number of rows/columns in the contingency table. |
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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3390/math11091982")}
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). New York: Routledge.
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()
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 <- 0.3
pwr::pwr.chisq.test(
w = fei_to_w(Fei, p = p0),
df = length(p0) - 1,
sig.level = 0.01,
power = 0.85
)
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