Learn R Programming

sjlabelled (version 1.2.0)

get_na: Retrieve tagged NA values of labelled variables

Description

This function retrieves tagged NA values and their associated value labels from a labelled vector.

Usage

get_na(x, as.tag = FALSE)

Arguments

x

Variable (vector) with value label attributes, including tagged missing values (see tagged_na()); or a data frame or list with such variables.

as.tag

Logical, if TRUE, the returned values are not tagged NA's, but their string representative including the tag value. See 'Examples'.

Value

The tagged missing values and their associated value labels from x, or NULL if x has no tagged missing values.

Details

Other statistical software packages (like 'SPSS' or 'SAS') allow to define multiple missing values, e.g. not applicable, refused answer or "real" missing. These missing types may be assigned with different values, so it is possible to distinguish between these missing types. In R, multiple declared missings cannot be represented in a similar way with the regular missing values. However, tagged_na() values can do this. Tagged NAs work exactly like regular R missing values except that they store one additional byte of information: a tag, which is usually a letter ("a" to "z") or character number ("0" to "9"). This allows to indicate different missings.

Furthermore, see 'Details' in get_values.

Examples

Run this code
# NOT RUN {
library(haven)
x <- labelled(c(1:3, tagged_na("a", "c", "z"), 4:1),
              c("Agreement" = 1, "Disagreement" = 4, "First" = tagged_na("c"),
                "Refused" = tagged_na("a"), "Not home" = tagged_na("z")))
# get current NA values
x
get_na(x)
# which NA has which tag?
get_na(x, as.tag = TRUE)

# replace only the NA, which is tagged as NA(c)
if (require("sjmisc")) {
  replace_na(x, value = 2, tagged.na = "c")
  get_na(replace_na(x, value = 2, tagged.na = "c"))

  # data frame as input
  y <- labelled(c(2:3, 3:1, tagged_na("y"), 4:1),
                c("Agreement" = 1, "Disagreement" = 4, "Why" = tagged_na("y")))
  get_na(data.frame(x, y))
}
# }

Run the code above in your browser using DataLab