tdata <- read.delim("data.txt", header=TRUE, sep="\t", na.strings="NA", dec=".", strip.white=TRUE)
# demographics
tdata_age <- tdata
min(tdata_age$Age)
## [1] 18
max(tdata_age$Age)
## [1] 75
mean(tdata_age$Age)
## [1] 34.94444
sd(tdata_age$Age)
## [1] 12.31927
# 1 = male, 2 = female, 3 = other
table(tdata$Sex)
##
## 1 2 3
## 89 125 2
1 = male, 2 = female, 3 = non-binary
myTheme <- theme(plot.title = element_text(face="bold", size = 22),
axis.title.x = element_blank(),
axis.title.y = element_text(face = "bold", size = 20),
axis.text.x = element_text(size = 18, angle = 0),
axis.text.y = element_text(size = 16, angle = 0),
legend.text = element_text(size = 18),
legend.title = element_text(face = "bold", size = 18),
strip.text.x = element_text(size = 18),
#panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line.x = element_line(colour = "black"),
axis.line.y = element_line(colour = "black"),
axis.text = element_text(colour ="black"),
axis.ticks = element_line(colour ="black"))
tdata_sub <- tdata_long
library(see)
## first, turn sID into a factor
tdata_sub$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(Query_order ~ Cause_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 \ncause", "Common \ncause", "No \ncause")) +
#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 = 0.2)+
geom_line(position = pd, color = "black", size = 1, alpha=0.04) +
geom_point(aes(color = variable), position = pd, alpha = 0.2) +
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 = "Number Cause's Effects", 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
#ggsave("results_lines.svg",width=6,height=4.3)
#ggsave("results_lines.pdf",width=6,height=4.3)
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"))
tdata_sub <- tdata_long
tdata_sub_graph <- subset(tdata_sub, variable == "CC" | variable == "SC")
library(see)
## first, turn sID into a factor
tdata_sub$sID <- factor(tdata_sub$sID)
pd <- position_dodge(width = 0.3)
tdata_sub_graph$valueJitter <- jitter(tdata_sub_graph$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_graph, aes(x=variable, y=valueJitter, group = sID)) +
guides(fill=FALSE)+
#facet_grid(Query_order ~ Cause_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 \ncause", "common \ncause", "No \ncause")) +
#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 = 0.2)+
geom_line(position = pd, color = "black", size = 1, alpha=0.04) +
geom_point(aes(color = variable), position = pd, alpha = 0.2) +
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 = "Number Cause's Effects", 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