Item-Objective Congruence (IOC) — ioc • contentvalidR

Computes item-objective congruence from expert ratings coded -1, 0, and +1. Duplicate item-judge-objective ratings are rejected. Missing ratings may be removed cellwise with transparent effective judge counts.

Usage

ioc(ratings, na.rm = FALSE)

Arguments

ratings: Data frame with columns item, judge, objective, score.
na.rm: Logical. If FALSE, missing scores are an error; if TRUE, missing scores are removed within item-objective cells.

Value

A data.frame with item, objective, total rows, effective judge count, missing count, and IOC.

References

Rovinelli, R. J., & Hambleton, R. K. (1977). On the use of content specialists in the assessment of criterion-referenced test item validity. Dutch Journal of Educational Research, 2, 49-60.

Turner, R. C., & Carlson, L. (2003). Indexes of item-objective congruence for multidimensional items. International Journal of Testing, 3(2), 163-171. doi:10.1207/S15327574IJT0302_5

Examples

df <- data.frame(
  item = rep("I1", 6),
  judge = rep(1:3, 2),
  objective = rep(c("A", "B"), each = 3),
  score = c(1,1,1, 0,-1,0)
)
ioc(df)
#>   item objective n_total n_judges n_missing        ioc
#> 1   I1         A       3        3         0  1.0000000
#> 2   I1         B       3        3         0 -0.3333333