vio_ses <- ggplot(df, aes(x = PartnerG, y = ARI))
geom_violin(adjust = 1.5) +
  geom_boxplot(width = .07, fill = "gray", outlier.colour = NA) +
  stat_summary(fun.y = mean, geom = "point", fill = "black", shape = 21, size = 2.5) +
  scale_y_continuous(breaks=seq(0,12,2))
  
library(dplyr)
df %>%
  group_by(sex_p) %>%
  summarise(group_data = list(ARI)) %>%
  wilcox.test(.$group_data[[1]], .$group_data[[2]]) %>%
  print()
USER_IDSEXAGEGRADEsiblingsnationalitypartner_pannual_income
1Female1243JapaneseMarried
2Female1453JapaneseMarried
3Male17111JapaneseMarried
Wilcoxon rank sum test with continuity correction
data: arj_male and arj_female
W = 288837, p-value = 0.4258
alternative hypothesis: true location shift is not equal to 0

Global Environment

  • ageDiff - List of 22
  • ARI_norm - num [1:4820] -0.674 ...
  • common_theme - List of 7

Files

  • .RData
  • .Rhistory
  • aa.png
  • ARI_IRT.csv
  • figures_Violin_plot_gender.png