MDISC

Returns a vector containing the MDISC values for each item in the model input object (Reckase, 2009).
Note that the logistic slope parameters are divided by 1.702 to match the normal ogive metric.

discrimination

Analysis of dichotomous and polytomous response data using
    unidimensional and multidimensional latent trait models under the Item
    Response Theory paradigm. Exploratory and confirmatory models can be
    estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory
    bi-factor and two-tier analyses are available for modeling item testlets.
    Multiple group analysis and mixed effects designs also are available for
    detecting differential item and test functioning as well as modelling
    item and person covariates.

MDISC: Compute multidimensional discrimination index

Description

Usage

Arguments

References

See Also

Examples