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Add Missing Value Flags to Health Indicators

Source: R/utils-quality_checks.R
add_missing_column.Rd

add_missing_column assesses data quality by identifying missing values for specified health indicators. It generates new columns for each indicator, flagging values as 'Missing' (1) or 'Non-Missing' (0) to support downstream quality control and analysis.

Usage

add_missing_column(.data, indicators)

Arguments

.data

A data frame containing health indicator data.

indicators

A character vector specifying the names of the indicator columns to analyze for outliers.

Value

A data frame containing:

  • Missingness Flags: For each indicator, a column prefixed with mis_ indicating missingness (1 for missing, 0 otherwise).

  • district and year columns to maintain grouping information.

Details

  • Missingness Assessment: Each indicator is processed to flag missing values (NA) with 1 (missing) or 0 (non-missing). The resulting columns are prefixed with mis_ followed by the original indicator name (e.g., mis_indicator1).

  • Group Preservation: The output retains the district and year columns to ensure grouping information remains intact.

Examples

if (FALSE) { # \dontrun{
  # dd missing value flags for all indicators
  add_missing_column(data)
} # }