Dichotomizing variables
Now that we've cleaned up our question names, let's work on the response variable. In the original analysis, they looked at the percent of people considering a behavior somewhat or very rude. To replicate this, we'll need to change our rude variable from the current responses to one that combines the somewhat and very rude answers.
Este ejercicio forma parte del curso
Categorical Data in the Tidyverse
Instrucciones del ejercicio
- Remove rows with NA in the value column
- Create a new variable, rude, which is 0 if the value column is "No, not rude at all" or "No, not at all rude" and 1 otherwise.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
dichotimized_data <- gathered_data %>%
mutate(response_var = str_replace(response_var, '.*rude to ', '')) %>%
mutate(response_var = str_replace(response_var, 'on a plane', '')) %>%
# Remove rows that are NA in the value column
___ %>%
# Dichotomize the value variable to make a new variable, rude
mutate(rude = if_else(value ___ c('No, not rude at all', 'No, not at all rude'), ___, ___))