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Shorten multiple text variables while giving NA codes.

Source: R/remove2NAchar.R
remove2NAchar.Rd

Shorten text variables from a certain number on while coding overflowing answers as complete missings.

Usage

remove2NAchar(GADSdat, vars, max_num = 2, na_value, na_label)

Arguments

GADSdat

A GADSdat object.

vars

A character vector with the names of the text variables.

max_num

Maximum number of text variables. Additional text variables will be removed and NA codes given accordingly.

na_value

Which NA value should be given in cases of too many values on text variables.

na_label

Which value label should be given to the na_value.

Value

Returns the modified GADSdat.

Details

In some cases, multiple text variables contain the information of one variable (e.g. multiple answers to an open item). If this is a case, sometimes the number text variables displaying this variable should be limited. remove2NAchar allows shortening multiple character variables, this means character variables after max_num are removed from the GADSdat. Cases, which had valid responses on these removed variables are coded as missings (using na_value and na_label).

Examples

## create an example GADSdat
example_df <- data.frame(ID = 1:4,
                        citizenship1 = c("German", "English", "missing by design", "Chinese"),
                        citizenship2 = c(NA, "German", "missing by design", "Polish"),
                        citizenship3 = c(NA, NA, NA, "German"),
                        stringsAsFactors = FALSE)
gads <- import_DF(example_df)

## shorten character variables
gads2 <- remove2NAchar(gads, vars = c("citizenship1", "citizenship2", "citizenship3"),
                      na_value = -99, na_label = "missing: too many answers")
#> Removing the following rows from meta data: citizenship3
#> No rows added to meta data.