CODEWITHSUNDEEP
rrecode
user13524734
user13524734

Reputation:

How to recode ordinal variable?

I am using survey data from the World Values Survey, I used the code below to change my variable from a numeric to an ordered variable

renameddata$Education= ordered(renameddata$Education, levels =c(-2,-1,840001,840002,840003,
                                         840004,840005,840006,840007,
                                         840008,840009),
        labels = c("NA","NA","LessHighSchool","SomeHighSchool",
                   "GED","SomeCollege","Associates","Bachelors",
                   "Masters","Professional","Doctorate"))

However, now I want to recode the education variable so that LessHighSchool and SomeHighSchool become one e.g "NO GED", and so that SomeCollege, Associates and Bachelors become "Undergraduate" etc.

Upvotes: 0

Views: 406

Answers (2)

DaveArmstrong
DaveArmstrong

Reputation: 21982

How about this:

library(dplyr)
renameddat <- renameddat %>% mutate(Education = 
        case_when(
          Education %in% c(840001,840002) ~ "No GED", 
          Education == 840003 ~ "GED", 
          Education %in% c(840004,840005,840006) ~ "Undergraduate", 
          Education %in% c(840007,840008,840009) ~ "Graduate", 
      TRUE ~ NA_character_), 
Education=factor(Education, 
                 levels=c("No GED", "GED", "Undergraduate", "Graduate")))

Upvotes: 1

deschen
deschen

Reputation: 10996

Alternatively, if you want to recode the created factor variable, you can use fct_collapse from the forcats package:

Input:

renameddata <- data.frame(Education = c(-2, -1, 840001, 840002, 840003, 840004, 840005, 840006, 840007, 840008, 840009))

renameddata$Education = ordered(renameddata$Education,
                                levels = c(-2, -1, 840001, 840002, 840003, 840004, 840005, 840006, 840007, 840008, 840009),
                                labels = c("NA", "NA", "LessHighSchool", "SomeHighSchool", "GED", "SomeCollege", "Associates", "Bachelors", "Masters", "Professional", "Doctorate"))

Recoding:

library(forcats)
renameddata$Education <- fct_collapse(renameddata$Education,
                                      "NO GED" = c("LessHighSchool", "SomeHighSchool"),
                                      "Undergraduate" = c("SomeCollege", "Associates", "Bachelors"))

gives:

       Education
1             NA
2             NA
3         NO GED
4         NO GED
5            GED
6  Undergraduate
7  Undergraduate
8  Undergraduate
9        Masters
10  Professional
11     Doctorate

Upvotes: 1

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