How to apply a shapiro test by groups in R?

Question

I have a dataframe where all my 90 variables have integer data, of the type:

code | variable1 | variable2 | variable3 | ...

AB | 2 | 3 | 10 |

Answer 1

The answer by @GegznaV was excellent but meanwhile, the tidyverse has some newer constructs like tidyr::pivot_longer replacing tidyr::gather, and the tidyverse authors recommend the nest-unnest syntax.

Also, I replaced broom::tidy by broom::glance as it gives the statistics for more models (e.g. aov()).

Here's the same example of @GegznaV rewritten in the updated tidyverse syntax:

library(tidyverse)
library(broom)

mtcars %>% 
  select(-am, -wt) %>%
  pivot_longer(
    cols = everything(),
    names_to = "variable_name",
    values_to = "value"
  ) %>% 
  nest(data = -variable_name) %>% 
  mutate(
    shapiro = map(data, ~shapiro.test(.x$value)),
    glanced = map(shapiro, glance)
  ) %>% 
  unnest(glanced) %>% 
  select(variable_name, W = statistic, p.value) %>% 
  arrange(variable_name)

which gives the same result:

# A tibble: 9 x 3
  variable_name     W      p.value
                   
1 carb          0.851 0.000438    
2 cyl           0.753 0.00000606  
3 disp          0.920 0.0208      
4 drat          0.946 0.110       
5 gear          0.773 0.0000131   
6 hp            0.933 0.0488      
7 mpg           0.948 0.123       
8 qsec          0.973 0.594       
9 vs            0.632 0.0000000974