Psychometric markers dispatcher

Usage

psych_markers(
  data,
  col_map = list(),
  which = c("phq9", "gad7", "k6", "k10", "ghq12_likert", "ghq12_binary", "who5", "isi",
    "mdq", "asrs", "bis", "spq", "cognitive", "dx_flags", "med_flags"),
  na_action = c("keep", "omit", "error"),
  missing_prop_max = 0.2,
  impute = c("none", "mean"),
  bis_key = NULL,
  spq_key = NULL,
  cognitive_method = c("z_mean", "pca1"),
  verbose = FALSE
)

Arguments

data: Data frame containing questionnaire item columns.
col_map: Nested list of mappings per instrument (e.g., col_map$phq9, col_map$bis, col_map$dx_flags, ...).
which: Vector of modules to compute (e.g., "phq9", "gad7", "bis").
na_action: How to handle rows with missing items: keep, omit, or error.
missing_prop_max: Maximum allowed proportion of missing items per row before the score is set to NA.
impute: Imputation strategy for missing items when under the threshold: none or mean (row-wise mean).
bis_key: SPQ/BIS key list passed to bis_score when requested.
spq_key: SPQ key list passed to spq_score when requested.
cognitive_method: Method passed to cognitive_score ("z_mean" or "pca1").
verbose: Logical flag for verbose messaging (reserved).

Value

A tibble of computed score columns from all requested modules, bound together. No input columns are included in the output.

Examples

df <- data.frame(
  phq9_01 = 0, phq9_02 = 1, phq9_03 = 2, phq9_04 = 1, phq9_05 = 0,
  phq9_06 = 1, phq9_07 = 2, phq9_08 = 1, phq9_09 = 0,
  gad7_01 = 0, gad7_02 = 1, gad7_03 = 2, gad7_04 = 1, gad7_05 = 0,
  gad7_06 = 1, gad7_07 = 2
)
psych_markers(df, which = c("phq9", "gad7"))
#> # A tibble: 1 × 4
#>   PHQ9_total PHQ9_severity GAD7_total GAD7_severity
#>        <dbl> <fct>              <dbl> <fct>        
#> 1          8 mild                   7 mild