# NOT RUN {
s1 <- labelled(c("M", "M", "F"), c(Male = "M", Female = "F"))
s1
str(s1)
s2 <- labelled(c(1, 1, 2), c(Male = 1, Female = 2),
label="Assigned sex at birth")
s2
str(s2)
# Unfortunately it's not possible to make as.factor() work for labelled objects
# so instead use to_factor(). This works for all types of labelled vectors.
to_factor(s1)
to_factor(s1, levels = "prefixed")
to_factor(s2)
# Other statistical software supports multiple types of missing values
s3 <- labelled_spss(c(1, 1, 2, 2, 8, 9),
c(Male = 1, Female = 2, Refused = 8, "Not applicable" = 9),
na_values = c(8, 9)
)
s3
str(s3)
to_factor(s3)
to_factor(s3, user_na_to_na = TRUE)
is.labelled(s1)
# }
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