Hinkin-Tracey distinctiveness (HTD)

Computes the Hinkin-Tracey distinctiveness index of Colquitt et al. (2019) for each item in a fully crossed, within-judge rating design. For every complete judge, the intended construct rating is contrasted with each orbiting-construct rating. The average of those difference scores is divided by a - 1, where a is the number of rating anchors. HTD ranges from -1 to 1.

HTD is therefore the intended construct's average lead over all the orbiting constructs, not its lead over any one of them. The other construct with the highest mean rating is reported beside it as strongest_competitor, with that mean as competitor_mean; both use the judges HTD uses, those who rated the item against every construct.

Usage

htd(
  ratings,
  item_col = "item",
  rater_col = "rater",
  construct_col = "construct",
  rating_col = "rating",
  target_map = NULL,
  target_col = "target_construct",
  scale_min = 1,
  scale_max = 5
)

Arguments

ratings

A long-format data.frame containing item, rater, construct, and rating columns.

item_col, rater_col, construct_col, rating_col

Column names.

target_map

Optional named item-to-target mapping.

target_col

Target column used when target_map is NULL.

scale_min, scale_max

Endpoints of the equally spaced integer rating scale.

Value

A data.frame containing item-level HTD, the strongest orbiting construct, complete-judge count, and number of target-orbiting pairs. It prints as a formatted table in APA style; the values themselves are unrounded, and as.data.frame() returns the plain data frame.

References

Colquitt, J. A., Sabey, T. B., Rodell, J. B., & Hill, E. T. (2019). Content validation guidelines: Evaluation criteria for definitional correspondence and definitional distinctiveness. Journal of Applied Psychology, 104(10), 1243–1265. doi:10.1037/apl0000406

Examples

d <- expand.grid(item = "I1", rater = 1:4, construct = c("A", "B", "C"))
d$rating <- c(5,4,5,4, 2,2,1,2, 3,2,2,1)
htd(d, target_map = c(I1 = "A"), scale_min = 1, scale_max = 5)
#> <contentvalid_htd> Hinkin-Tracey distinctiveness (HTD)
#> Colquitt et al. (2019).
#> 
#>   Item  Target  Judges  Target mean  Competitor  Competitor mean  HTD
#>   I1    A            4         4.50  C                      2.00  .66
#> 
#> Competitor: the other construct with the highest mean rating. HTD itself
#> averages the gap over every other construct.
#> 
#> See as.data.frame(x) for the unrounded values.