set.seed(2)
library('tidyverse')
library('ordinal')
n_per_group <- 50
dat <- tibble(
group = rep(c('A', 'B'), each = n_per_group),
rating = c(
rep(1:5, rmultinom(1, n_per_group, c(0.2, 0.3, 0.3, 0.1, 0.1))),
rep(1:5, rmultinom(1, n_per_group, c(0.1, 0.1, 0.3, 0.3, 0.2)))
)
)
# T-test:
t.test(rating ~ group, data = dat)
Welch Two Sample t-test
data: rating by group
t = -1.8735, df = 95.277, p-value = 0.06406
alternative hypothesis: true difference in means between group A and group B is not equal to 0
95 percent confidence interval:
-1.02980226 0.02980226
sample estimates:
mean in group A mean in group B
2.7 3.2 # Mann-Whitney-U-test:
wilcox.test(rating ~ group, data = dat)
Wilcoxon rank sum test with continuity correction
data: rating by group
W = 992, p-value = 0.0692
alternative hypothesis: true location shift is not equal to 0# Ordinal (Proportional odds) regression:
fm <- clm(factor(rating) ~ group, data = dat)
summary(fm)formula: factor(rating) ~ group
data: dat
link threshold nobs logLik AIC niter max.grad cond.H
logit flexible 100 -156.88 323.77 4(0) 1.09e-08 2.5e+01
Coefficients:
Estimate Std. Error z value Pr(>|z|)
groupB 0.6710 0.3636 1.845 0.065 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Threshold coefficients:
Estimate Std. Error z value
1|2 -1.38566 0.30796 -4.500
2|3 -0.03328 0.25658 -0.130
3|4 1.00185 0.28384 3.530
4|5 1.82059 0.33024 5.513