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Plotting individual estimates
if (!require("pacman")) install.packages("pacman")
pacman::p_load("ggplot2", "Rmisc")
#############################################################
# Preparing data (you can skip this and go to the plot : )
#############################################################
# Simulate some date by trial
parts = 30 # Our participants
trials = 60 # Our Trials
df=data.frame()
# Simulate some date by trial
parts = 30 # Our participants
trials = 60 # Our Trials
conds = 2 # How many conditions we have
df=data.frame()
for(i in 1:30 ){
# As I'm not focusing on simulatng realistic data, the responses are totally trivial
mean = rnorm(1, 0.5, 1)
response1 = rnorm(trials/2, mean = mean, sd = sd)
response2 = rnorm(trials/2, mean = mean - runif(1, 0.1, 0.4), sd = sd)
response <- c(response1, response2)
type = c(rep("a", 30), rep("b", 30))
cond = "A"
df2 = data.frame( part = rep(i, 60), cond = rep(cond, 60), type = type, RT = response)
df=rbind(df, df2)
}
for(i in 30:60 ){
mean = rnorm(1, 0.5, 3)
sd = runif(1, 2, 5)
response1 = rnorm(trials/2, mean = mean, sd = sd)
response2 = rnorm(trials/2, mean = mean - runif(1, 0.5, 4), sd = sd)
response <- c(response1, response2)
type = c(rep("a", 30), rep("b", 30))
cond = "B"
df2 = data.frame( part = rep(i, 60), cond = rep(cond, 60), type = type, RT = response)
df=rbind(df, df2)
}
#############################################################
# Prepare the data
#############################################################
tab = summarySEwithin(data = df, measurevar = "RT",
withinvars = c("type", "part"), betweenvars = "cond")
# Get the mean of each participant in both types.
# this is just for ordering the data
tab = tab %>% group_by(part) %>%
summarise(mean_rt = mean(RT)) %>%
left_join(tab, . )
# Ordering by mean RT
tab = arrange(tab, desc(mean_rt), part)
#############################################################
# Do the plot
#############################################################
pd <- position_dodge(0.4)
# Change them values to do a clean one
theme_set(theme_bw())
my_theme <- theme(panel.grid.major.x = element_blank(),
panel.grid.minor.x= element_blank(),
panel.background = element_blank(),
panel.border = element_blank(),
strip.text.x = element_text(size=14), strip.text.y = element_text(size=16),
strip.background = element_rect(colour="black"),
axis.text.x = element_text(color="black", size=14),
axis.text.y = element_text(color="black", size=14),
axis.title.x = element_text(face="bold", size=18),
axis.title.y = element_text(face="bold",size=18),
axis.ticks = element_blank(),
legend.title = element_text(size=14), legend.text = element_text(size = 14),
plot.title = element_text(vjust = 1.3, face="bold", size=20),
plot.margin = unit(c(1.5, 1.5, 1.5, 1.5), "cm")
)
ggplot(tab, aes(x = reorder(part, -mean_rt), y = RT, group = type, col = type)) +
geom_point(position=pd) +
coord_flip() + facet_wrap(~cond) +
ylab("RT") + xlab("Participant") + ggtitle("Reaction times") +
geom_linerange(aes(ymin= RT-se, ymax= RT+se), size = 1, position = pd) +
my_theme +
theme(axis.text.y = element_blank(),
legend.position = c(.9,.8))
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