
This function tries to return the best effect-size measure for the provided input model. See details.
effectsize(model, ...)
An object of class htest
, or a statistical model. See details.
Arguments passed to or from other methods. See details.
For an object of class htest
:
A t-test returns Cohen's d via t_to_d()
.
A correlation test returns r. See t_to_r()
.
A Chi-squared test returns Cramer's V via cramers_v()
.
A One-way ANOVA test returns Eta squared via F_to_eta2()
, but can be changes via an es
argument.
For an object of class BFBayesFactor
, using bayestestR::describe_posterior()
,
A t-test returns Cohen's d.
A correlation test returns r..
A contingency table test returns Cramer's V.
Objects of class anova
, aov
, or aovlist
are passed to eta_squared()
.
Other objects are passed to standardize_parameters()
.
For statistical models it is recommended to directly use the listed functions, for the full range of options they provide.
# NOT RUN {
contingency_table <- as.table(rbind(c(762, 327, 468), c(484, 239, 477), c(484, 239, 477)))
Xsq <- chisq.test(contingency_table)
effectsize(Xsq)
Ts <- t.test(1:10, y = c(7:20))
effectsize(Ts)
Aov <- oneway.test(extra ~ group, data = sleep)
effectsize(Aov)
if (require(BayesFactor)) {
bf1 <- ttestBF(mtcars$mpg[mtcars$am == 1], mtcars$mpg[mtcars$am == 0])
effectsize(bf1, test = NULL)
bf2 <- correlationBF(iris$Sepal.Length, iris$Sepal.Width)
effectsize(bf2, test = NULL)
data(raceDolls)
bf3 <- contingencyTableBF(raceDolls, sampleType = "poisson", fixedMargin = "cols")
effectsize(bf3, test = NULL)
}
fit <- lm(mpg ~ factor(cyl) * wt + hp, data = mtcars)
effectsize(fit)
anova_table <- anova(fit)
effectsize(anova_table)
# }
Run the code above in your browser using DataLab