Define a scored scale

Creates a scale definition that groups items and specifies how composite scores are computed. The scale carries scoring rules used by score_scales() and measurement structure used by reliability_report(), item_report(), and cfa_syntax().

Usage

sf_scale(
  id,
  label,
  items,
  method = c("mean", "sum"),
  min_valid = NULL,
  reverse_items = NULL,
  weights = NULL
)

Arguments

id

Character. A unique identifier for this scale. Referenced in the scale_id argument of sf_item().

label

Character. A human-readable name for the scale, used in reports and codebooks.

items

Character vector. The id values of items that belong to this scale, each listed once. Order controls presentation in reports, while scoring uses the same item IDs regardless of order. Items themselves are passed to sf_instrument() as separate components.

method

Character. Scoring method. Either "mean" (default) or "sum".

min_valid

Integer or NULL. The minimum number of answered items required to compute a score for a respondent, a whole number from 1 to the number of items. When NULL, every item must be answered. An item whose column is absent from the data counts as unanswered. Used by score_scales().

reverse_items

Character vector or NULL. A subset of items that this scale reverse-codes. Reversal applies within this scale only, so the same item can be reversed in one scale and scored as answered in another. An item can also be flagged with reverse = TRUE in sf_item(), which reverses it within the scale named by its scale_id. A reversed item needs declared response bounds, from a numeric choice set, slider limits or a rating maximum.

weights

Numeric vector or NULL. Item weights for weighted scoring, one positive finite number per item, in the order of items. score_scales() applies the weights to either method = "mean" or method = "sum".

Value

An object of class sf_scale (a named list).

See also

sf_item(), score_scales(), reliability_report()

Examples

sat_scale <- sf_scale(
  id            = "satisfaction",
  label         = "Customer Satisfaction",
  items         = c("sat_overall", "sat_speed", "sat_quality"),
  method        = "mean",
  min_valid     = 2,
  reverse_items = NULL
)