Add Median and MAD Columns for Indicators

add_mad_med_columns calculates and appends the median and Median Absolute Deviation (MAD) for specified indicators in a dataset. These statistics are calculated per group, allowing the user to dynamically group data (e.g., by district) and exclude data from the most recent year in the dataset.

Usage

add_mad_med_columns(.data, indicators, group_by = "district")

Arguments

.data

A cd_data tibble containing health indicator data.

indicators

A character vector specifying the names of the indicator columns for which the median and MAD should be calculated.

group_by

A character string or vector specifying the column(s) to group by when calculating the median and MAD (default is 'district').

Value

A tibble with additional columns for each indicator, named {indicator}_med and {indicator}_mad, containing the calculated median and MAD, respectively.

Details

• The median and MAD are calculated for each group specified by group_by.

• Only data from years prior to the most recent year in the dataset are considered.

• Missing values in the calculated statistics are replaced using robust_max(), ensuring that meaningful fallback values are provided.

See also

• add_outlier5std_column() for generating outlier flags based on these columns.

• robust_max() for calculating max value

Examples

if (FALSE) { # \dontrun{
  # Add median and MAD columns for 'indicator1'
  add_mad_med_columns(data, indicators = 'indicator1',
                    group_by = 'district')
} # }