Clean and filter GBD data for QCI computation

Performs the standard data preparation steps:

1. Remove specified location IDs (e.g., 533 for Melanesia aggregate)

2. Standardize measure names (shorten verbose GBD names)

3. Filter to specified countries using location_type metadata

4. Filter to specified age categories

5. Filter to Rate metric and reshape to wide format

Usage

qci_clean(
  data,
  loc_types = NULL,
  keep_types = "Country",
  age_categories = "Age-standardized",
  exclude_location_ids = 533L
)

Arguments

data

A data.frame or data.table of raw GBD data (output of qci_load()).

loc_types

A data.frame of location metadata. If NULL, uses the bundled location_type dataset.

keep_types

Character vector of location types to retain. Default "Country". Use NULL to skip location type filtering.

age_categories

Character vector of age groups to include. Default "Age-standardized".

exclude_location_ids

Integer vector of location_ids to exclude. Default 533.

Value

A list with two data.table elements:

wide_rate

Wide-format data for Rate metric, used for the final merged output.

wide_number

Wide-format data used for ratio/PCA computation. Uses Rate data (ratios of rates equal ratios of numbers).

Each has columns like val_Deaths, val_Incidence, upper_Deaths, lower_Deaths, etc.

Examples

data(sample_gbd)
cleaned <- qci_clean(sample_gbd)
#> ✔ Cleaned data: 9 locations, 3 years.
names(cleaned)
#> [1] "wide_rate"   "wide_number"