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.
Diese Übung ist Teil des Kurses
Categorical Data in the Tidyverse
Anleitung zur Übung
- 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.
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
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'), ___, ___))