# NOT RUN {
## Hypothesis Testing
## ------------------
contingency_table <- as.table(rbind(c(762, 327, 468), c(484, 239, 477), c(484, 239, 477)))
Xsq <- chisq.test(contingency_table)
effectsize(Xsq)
effectsize(Xsq, type = "phi")
Tt <- t.test(1:10, y = c(7:20), alternative = "less")
effectsize(Tt)
Aov <- oneway.test(extra ~ group, data = sleep, var.equal = TRUE)
effectsize(Aov)
effectsize(Aov, type = "omega")
Wt <- wilcox.test(1:10, 7:20, mu = -3, alternative = "less")
effectsize(Wt)
effectsize(Wt, type = "cles")
## Bayesian Hypothesis Testing
## ---------------------------
# }
# NOT RUN {
if (require(BayesFactor)) {
bf_prop <- proportionBF(3, 7, p = 0.3)
effectsize(bf_prop)
bf_corr <- correlationBF(attitude$rating, attitude$complaints)
effectsize(bf_corr)
data(raceDolls)
bf_xtab <- contingencyTableBF(raceDolls, sampleType = "poisson", fixedMargin = "cols")
effectsize(bf_xtab)
effectsize(bf_xtab, type = "oddsratio")
bf_ttest <- ttestBF(sleep$extra[sleep$group==1],
sleep$extra[sleep$group==2],
paired = TRUE, mu = -1)
effectsize(bf_ttest)
}
# }
# NOT RUN {
## Models and Anova Tables
## -----------------------
fit <- lm(mpg ~ factor(cyl) * wt + hp, data = mtcars)
effectsize(fit)
anova_table <- anova(fit)
effectsize(anova_table)
effectsize(anova_table, type = "epsilon")
# }
Run the code above in your browser using DataLab