Psi Chi R Sponsored Workshop: Tiny Tasks in R (APS 2024)

Source: Psi Chi APS 2024

Load packages and import data

library(tidyverse)

dataset=read.csv('https://osf.io/download/pr4ws/')

Check the data

head(dataset)

#skimr::skim(dataset)

Preparing the data

1. Remove participants who are missing ‘Age’

dataset1=dataset %>% 
  filter(!is.na(Age))

#sum(!complete.cases(dataset$Age))

2. Remove participants who are missing ‘Gender’

dataset2=dataset1 %>% 
  filter(!is.na(Gender))

#sum(!complete.cases(dataset1$Gender))

3. Create the following variable ‘FACEenmesh’ which measures the extent to which a family is enmeshed, by summing the following items: FACES4, FACES10, FACES16, FACES22, FACES28, FACES34, FACES40

dataset3=dataset2 %>% 
  mutate(FACEenmesh = FACES4 + FACES10 + FACES16 + FACES22 + FACES28 + FACES34 + FACES40) %>% 
  select(FACEenmesh,everything())

4. Identify participants with values considered outliers for ‘FACEenmesh’

dataset3 %>% 
  ggplot(aes(x=FACEenmesh))+
  geom_boxplot()

dataset3 %>% 
  filter(!is.na(FACEenmesh)) %>% 
  summarise(mean(FACEenmesh),
            median(FACEenmesh),
            min(FACEenmesh),
            max(FACEenmesh),
            sd(FACEenmesh))

dataset3.5 = dataset3 %>% 
  filter(!is.na(FACEenmesh),
         FACEenmesh > 25)

dataset3.5

5. Remove participants with values considered outliers on ‘FACEenmesh’

dataset4 = dataset3 %>% 
  filter(!is.na(FACEenmesh),
         FACEenmesh < 25)

dataset4 %>% 
  ggplot(aes(x=FACEenmesh))+
  geom_boxplot()

dataset4 %>% 
  ggplot(aes(x=FACEenmesh))+
  geom_density()

Descriptives

1. Find the mean of ‘FACEenmesh’
2. Find the standard deviation of ‘FACEenmesh’
3. Find the median of ‘FACEenmesh’
4. Find the range of ‘FACEenmesh’

dataset4 %>% 
  summarise(mean(FACEenmesh),
            sd(FACEenmesh),
            median(FACEenmesh),
            min(FACEenmesh),
            max(FACEenmesh),
            range(FACEenmesh))