Assumes that per‑dimension severity scores have already been computed and added to df
by earlier functions: add_prot_score_movement()
, add_prot_score_practices()
, and add_prot_score_rights()
.
This function performs only Step 4 of the 2025 Protection Composite workflow: it takes the maximum of those three existing columns to create comp_prot_score
, then generates binary “in need” indicators.
Arguments
- df
A
data.frame
ortibble
containing numeric columns:comp_prot_score_movement
– severity for movement dimensioncomp_prot_score_practices
– severity for practices dimensioncomp_prot_score_rights
– severity for rights & services dimension
If any of these three columns are missing, the function will abort, reminding you to run the corresponding prep functions first.
Value
The input df
, with three new columns:
comp_prot_score
– overall protection severity (maximum of the three dimensions)comp_prot_in_need
– binary (0/1): 1 ifcomp_prot_score >= 3
, else 0comp_prot_in_acute_need
– binary (0/1): 1 ifcomp_prot_score >= 4
, else 0
Details
Column checks via
purrr::iwalk()
ensure the three dimension scores exist.Computation uses
pmax()
(withna.rm = FALSE
)Thresholds (3 for “in need”, 4 for “acute need”) are currently hard‑coded.