GHQ-12 scoring (Likert or binary)

Usage

ghq12_score(
  data,
  col_map = list(),
  na_action = c("keep", "omit", "error"),
  missing_prop_max = 0.2,
  impute = c("none", "mean"),
  prefix = "GHQ12",
  method = c("likert", "binary"),
  case_cutoff_binary = 3,
  verbose = FALSE
)

Arguments

data: Data frame containing questionnaire item columns.
col_map: Named list mapping canonical item IDs to column names; defaults assume items are already named.
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).
prefix: Prefix for output column names.
method: Scoring method: likert (0-3 per item) or binary (0/1 per item).
case_cutoff_binary: Cut-off for case status when using binary scoring.
verbose: Logical flag for verbose messaging (reserved).

Value

A tibble of score columns only: GHQ12_total_likert (likert method) or GHQ12_total_binary and GHQ12_case_binary (binary method). Input columns are not included.

Examples

df <- data.frame(ghq12_01 = 0, ghq12_02 = 1, ghq12_03 = 2, ghq12_04 = 1,
                 ghq12_05 = 0, ghq12_06 = 1, ghq12_07 = 0, ghq12_08 = 1,
                 ghq12_09 = 2, ghq12_10 = 1, ghq12_11 = 0, ghq12_12 = 1)
ghq12_score(df, method = "likert")
#> # A tibble: 1 × 1
#>   GHQ12_total_likert
#>                <dbl>
#> 1                 10