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Check for uniqueness and non-missingness in an identifier variable

check_id.Rd

This function checks whether an identifier variable in a GADSdat object meets key requirements for data quality:

  • The identifier variable must be unique (i.e., no duplicate values).

  • The identifier variable must not contain any missing values (NA).

These checks help ensure that the identifier variable can uniquely and reliably index rows within the data.

Usage

check_id(GADSdat, idVar = NULL)

Arguments

GADSdat

A GADSdat object containing the data to be checked.

idVar

A character string specifying the name of the identifier variable in the GADSdat object. If NULL, the first variable in the dataset will be used as the identifier variable.

Value

A list with two components summarizing the issues found:

  • missing_ids: A data.frame with the row indices of observations where the identifier variable has missing values.

  • duplicate_ids: A data.frame with the values of duplicate identifiers (if any).

If there are no missing or duplicate identifiers, the respective data.frame will be empty.

Examples

# Example usage

# Load example GADSdat object
GADSdat <- eatGADS::import_spss(system.file("extdata", "example_data2.sav", package = "eatFDZ"))

# Check identifier variable for uniqueness and non-missingness
id_check <- check_id(GADSdat, idVar = "ID")

# View rows with missing identifier values
print(id_check$missing_ids)
#>   Rows
#> 1   12

# View duplicate identifier values
print(id_check$duplicate_ids)
#>        ID
#> 11 SH0886