Link item parameters onto a target scale

Applies mean-mean linking to express source item parameters on the scale of a target calibration. Both parameter sets must be in slope-intercept form for the model plogis(d + a * theta).

Usage

link_item_parameters(source, target, method = c("mean_mean", "none"))

Arguments

source

Item parameters to transform. A matrix or data frame with columns a/a1 and d, or a fitted mirt model.

target

Item parameters defining the target scale. Uses the same accepted formats as source.

method

Linking method. Currently "mean_mean" and "none" are supported.

Value

A list with transformed pars, linking constants A and B, and the selected method.

Details

If theta_target = A * theta_source + B, then source parameters transform as a_target = a_source / A and b_target = A * b_source + B, with d_target = -a_target * b_target. Mean-mean linking chooses A and B so that the transformed source parameters match the target mean discrimination and mean difficulty.

Examples

source <- data.frame(a = c(0.8, 1.2), d = c(-0.2, 0.5))
target <- data.frame(a = c(1.0, 1.5), d = c(-0.1, 0.4))
link_item_parameters(source, target)$pars
#>   item   a          d          b
#> 1    1 1.0 -0.1833333  0.1833333
#> 2    2 1.5  0.5250000 -0.3500000