Relationships between Big Five Personality Traits & Context

Culture and Decision Science Network Lab at ASU

Joshua Geenen

compiled on May 12, 2022

#longData <- read_csv('cameron-longData1.xlsx', na=".",col_names=TRUE)

### Create Names
names(data) <- paste(c("Study 1", "Study 2", "Study 3"))

### Create table of samples sizes and remove row of sample sizes from data frame
sampleSize <- data[1,]
sampleSize <- data.frame(n = unlist(transpose(as.vector(sampleSize))))
sampleSize$whichEvent <- row.names(sampleSize)

## Remove row
data <- data[-1,]

### Create columns with labels for correlations
data$trait <- rep(c("O", "C", "E", "A", "N"), each = 3)
data$Contexts <- rep(c("OFF/NC",
                       "SM/NC",
                       "SM/OFF"), times=5)


### Reshape data for plotting (tidyr)
longData <- data %>%
  pivot_longer(col = starts_with(c("Study 1", "Study 2", "Study 3")), 
               names_to = "whichEvent", values_to = "correlation") %>%
  separate(whichEvent, into = c("Study"), sep="_", remove = FALSE)

## Add Sample Size
longData <- left_join(longData, sampleSize, by = "whichEvent")

## Calculate confidence intervals
longData <- longData %>%
  mutate(z = .5 * log((1 + correlation)/(1 - correlation)),  ## Z
         se = 1/sqrt(n - 3),                                 ## SE
         upperz = z + qnorm(.025, lower.tail=FALSE)*se,      ## upper CI for Z
         lowerz = z - qnorm(.025, lower.tail=FALSE)*se,      ## lower CI for Z
         upperr = (exp(2*upperz) - 1) / (exp(2*upperz) + 1), ## upper CI for r
         lowerr = (exp(2*lowerz) - 1) / (exp(2*lowerz) + 1)) ## lower CI for r


longData$trait <- factor(longData$trait, levels=c("O", "C", "E", "A", "N"))

plot1 <-
  ggplot(longData,
         aes(x = Contexts, y = correlation, ymin = lowerr, 
             ymax=upperr, color=trait, shape=trait)) +
  scale_shape_manual(values=c(4, 15, 16, 17, 18))+
  scale_color_grey()+
  geom_pointrange(position = position_dodge(width=.5)) +
  geom_hline(yintercept=0, lty=2) +
  scale_y_continuous(limits = c(.00, 1.00)) +
  xlab("Contexts") + ylab("r (95%CI)") +
  ggtitle("Associations between contexts and personality traits") +
  facet_wrap(~Study, nrow=3) +
  theme_bw()+
  theme(axis.text.x = element_text(size = 10, angle=0))
print(plot1)

plot2 <-
  ggplot(longData,
         aes(x = Contexts, y = correlation, ymin = lowerr, 
             ymax=upperr, color=trait, shape=trait)) +
  scale_shape_manual(values=c(4, 15, 16, 17, 18))+
  scale_color_grey()+
  geom_pointrange(position = position_dodge(width=.5)) +
  geom_hline(yintercept=0, lty=2) +
  scale_y_continuous(limits = c(.00, 1.00)) +
  xlab("Contexts") + ylab("r (95%CI)") +
  ggtitle("Associations between contexts and personality traits") +
  theme_bw()+
  theme(axis.text.x = element_text(size = 10, angle=0))
print(plot2)