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Score the HiTOP-BR Instrument

Source: R/score_hitopbr.R
score_hitopbr.Rd

Create a data frame with scores on all the HiTOP-BR scales.

Usage

score_hitopbr(
  data,
  items,
  srange = c(1, 4),
  prefix = "hbr_",
  missing = c("available", "complete"),
  calc_se = FALSE,
  append = TRUE
)

Arguments

data

A data frame containing all HiTOP-BR items (numerically coded).

items

A vector of column names (as strings) or numbers (as integers) corresponding to the 45 HiTOP-BR items in order. Items must be supplied in instrument order; a misordered mapping silently scores the wrong items, so a warning is issued when the names share a common prefix and trailing number but those numbers are not ascending. Duplicated entries are an error.

srange

An optional numeric vector specifying the minimum and maximum values of the HiTOP-BR items, used for reverse-coding. (default = c(1, 4))

prefix

An optional string to add before each scale column name. If no prefix is desired, set to an empty string "". (default = "hbr_")

missing

A string selecting how missing item responses are handled when computing scale scores. "available" (the default) averages whatever items are present (rowMeans(na.rm = TRUE)); "complete" returns NA for any scale with a missing item (rowMeans(na.rm = FALSE)). (default = "available")

calc_se

An optional logical indicating whether to calculate the standard error of each scale score. (default = FALSE)

append

An optional logical indicating whether the new columns should be added to the end of the data input. (default = TRUE)

Value

A tibble containing all scale scores and standard errors (if requested) and all original data columns (if requested).

Details

For per-scale reliability estimates (Cronbach's alpha, McDonald's omega), use reliability_hitopbr().

Examples

# Score all HiTOP-BR scales from the simulated data
score_hitopbr(sim_hitopbr, items = 1:45, append = FALSE)
#> # A tibble: 100 × 8
#>    hbr_antagonism hbr_detachment hbr_disinhibition hbr_internalizing
#>             <dbl>          <dbl>             <dbl>             <dbl>
#>  1           2.56           2.5               1.67              2.29
#>  2           2.11           1.67              2.67              2.57
#>  3           2.44           3                 2.22              2.14
#>  4           2.67           2.33              2.22              2.29
#>  5           2.78           2.17              2.78              2   
#>  6           2              2.5               3.22              2.86
#>  7           2.44           2.17              3.11              2.29
#>  8           2.78           2.17              2.33              2.43
#>  9           1.89           2.67              2.67              2.43
#> 10           2.89           2                 2.78              2.71
#> # ℹ 90 more rows
#> # ℹ 4 more variables: hbr_somatoform <dbl>, hbr_thoughtDisorder <dbl>,
#> #   hbr_externalizing <dbl>, hbr_pFactor <dbl>