1 Results

1.1 Demographics

# demographics 

# one participant indicated 3 for age. Needs to be excluded for the age analysis.
tdata_age <- tdata 

min(tdata_age$Age)
## [1] 18
max(tdata_age$Age)
## [1] 60
mean(tdata_age$Age)
## [1] 32.16667
sd(tdata_age$Age)
## [1] 10.82118
# 1 = male, 2 = female, 3 = other
table(tdata$Sex)
## 
##  1  2  3 
## 45 71  4

2 Graphs

myTheme <- theme(plot.title = element_text(face="bold", size = 22),
        axis.title.x = element_blank(),
        axis.title.y = element_text(face = "bold", size = 20),
        axis.text.x = element_text(size = 18, angle = 0), 
        axis.text.y = element_text(size = 16, angle = 0),
        legend.text = element_text(size = 18),
        legend.title = element_text(face = "bold", size = 18),
        strip.text.x = element_text(size = 18),
        #panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(), 
        panel.background = element_blank(), 
        axis.line.x = element_line(colour = "black"), 
        axis.line.y = element_line(colour = "black"),
        axis.text = element_text(colour ="black"), 
        axis.ticks = element_line(colour ="black"))


library(see)
## first, turn sID into a factor
tdata_sub$sID <- factor(tdata_sub$sID)

pd <- position_dodge(width = 0.3)

tdata_sub$valueJitter <- jitter(tdata_sub$value, factor = 1, amount = 0.04)

theme_set(theme_light(base_size = 20, base_family = "Poppins"))

# new labes for the facets 

g <- ggplot(tdata_sub, aes(x=variable, y=valueJitter, group = sID)) +
  guides(fill=FALSE)+
  #facet_grid( ~ Side + Q_order)+
  #ggtitle("Subjects' causal srength ratings") +
  scale_y_continuous(limits = c(-0.05, 1.05), breaks=seq(0, 1, 0.1), expand = c(0,0)) +
  scale_x_discrete(labels=c("single-effect \n cause", "common \n cause")) +
  #stat_summary(fun.y = mean, geom = "bar", position = "dodge", colour = "black", alpha =0.5) +
  geom_violinhalf(aes(y = value, group = variable, fill = variable), color = NA, position=position_dodge(1), alpha = 0.3)+
  geom_line(position = pd, color = "black", size = 1, alpha=0.07) +
  geom_point(aes(color = variable), position = pd, alpha = 0.4, size = 2) +
  stat_summary(aes(y = value,group=1), fun.data = mean_cl_boot, geom = "errorbar", width = 0, size = 1) +
  stat_summary(aes(y = value,group=1), fun.y=mean, colour="black", geom="line",group=1, size = 1.5, linetype = "solid", alpha = 1)+
  stat_summary(aes(y = value,group=1, fill = variable), fun.y=mean, geom="point", color = "black", shape = 22, size = 5, group=1, alpha = 1)+
  stat_summary(aes(y = value,group=1), fun.y=median, geom="point", color = "black", shape = 3, size = 4, group=1, alpha = 1, position = position_dodge(width = 0.5))+
  labs(x = "Target Cause", y = "Causal Strength Rating") +
  scale_color_manual(name = "Entity",values=c("#fc9272", "#3182bd"))+
  scale_fill_manual(name = "Entity",values=c("#fc9272", "#3182bd"))+
  theme(legend.position = "none")+
  myTheme
## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.
## Warning: `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
g