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The classical companion table conventionally reported alongside a Rasch analysis (Andrich and Marais 2019, chs. 3-5), on complete cases only: per item the facility (mean score over maximum), the item-total and corrected item-rest correlations, the discrimination index DI = PRU - PRL (mean proportion-of-maximum in the upper third of total scores minus the lower third), and alpha if the item is deleted; plus coefficient alpha, the raw-score mean, SD, and the classical standard error of measurement \(s\sqrt{1 - \alpha}\), which unlike the Rasch SE is one value for all persons.

Usage

ctt_table(fit)

Arguments

fit

A fitted object from rasch.

Value

A list of class "rasch_ctt": the per-item table (item, n, min, max, facility, item_total, item_rest, di, alpha_drop), and the scalars alpha, n (complete cases), mean, sd, and sem.

Examples

set.seed(1)
d <- seq(-2, 2, length.out = 8)
X <- matrix(rbinom(400 * 8, 1, plogis(outer(rnorm(400), d, "-"))), 400, 8)
colnames(X) <- paste0("I", 1:8)
ctt_table(rasch(X))
#> Traditional statistics (available cases; item n 400-400; 400 complete)
#> Raw score mean 4.08, SD 1.71 (complete responders); alpha 0.529; SEM 1.17
#>  item   n min max facility item_total item_rest    di alpha_drop
#>    I1 400   0   1    0.848      0.370     0.169 0.298      0.519
#>    I2 400   0   1    0.787      0.443     0.221 0.373      0.504
#>    I3 400   0   1    0.672      0.479     0.226 0.484      0.504
#>    I4 400   0   1    0.575      0.526     0.267 0.589      0.488
#>    I5 400   0   1    0.432      0.579     0.333 0.663      0.460
#>    I6 400   0   1    0.338      0.495     0.243 0.497      0.497
#>    I7 400   0   1    0.250      0.533     0.313 0.527      0.472
#>    I8 400   0   1    0.175      0.407     0.198 0.316      0.511