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Recode a variable.

Source: R/recodeGADS.R
recodeGADS.Rd

Recode a variable as part of a GADSdat or all_GADSdat object.

Usage

recodeGADS(
  GADSdat,
  varName,
  oldValues,
  newValues,
  existingMeta = c("stop", "value", "value_new", "drop", "ignore")
)

Arguments

GADSdat

GADSdat object imported via eatGADS.

varName

Name of the variable to be recoded.

oldValues

Vector containing the old values.

newValues

Vector containing the new values (in the respective order as oldValues).

existingMeta

If values are recoded, which meta data should be used (see details)?

Value

Returns a GADSdat.

Details

Applied to a GADSdat or all_GADSdat object, this function is a wrapper of getChangeMeta and applyChangeMeta. Beyond that, unlabeled variables and values are recoded as well. oldValues and newValues are matched by ordering in the function call.

If changes are performed on value levels, recoding into existing values can occur. In these cases, existingMeta determines how the resulting meta data conflicts are handled, either raising an error if any occur ("stop"), keeping the original meta data for the value ("value"), using the meta data in the changeTable and, if incomplete, from the recoded value ("value_new"), or leaving the respective meta data untouched ("ignore").

Furthermore, one might recode multiple old values in the same new value. This is currently only possible with existingMeta = "drop", which drops all related meta data on value level, or existingMeta = "ignore", which leaves all related meta data on value level untouched.

Missing values (NA) are supported in oldValues but not in newValues. For recoding values to NA see recode2NA instead. For recoding character variables, using lookup tables via createLookup is recommended. For changing value labels see changeValLabels.

Examples

# Example gads
example_df <- data.frame(ID = 1:5, color = c("blue", "blue", "green", "other", "other"),
                        animal = c("dog", "Dog", "cat", "hors", "horse"),
                        age = c(NA, 16, 15, 23, 50),
                        stringsAsFactors = FALSE)
example_df$animal <- as.factor(example_df$animal)
gads <- import_DF(example_df)

# simple recode
gads2 <- recodeGADS(gads, varName = "animal",
                   oldValues = c(3, 4), newValues = c(7, 8))