IRT.cv

This S3 method performs a cross-validation of a fitted item response model.

Includes marginal maximum likelihood estimation and joint maximum
likelihood estimation for unidimensional and multidimensional
item response models. The package functionality covers the
Rasch model, 2PL model, 3PL model, generalized partial credit model,
multi-faceted Rasch model, nominal item response model,
structured latent class model, mixture distribution IRT models,
and located latent class models. Latent regression models and
plausible value imputation are also supported. For details see
Adams, Wilson and Wang, 1997 <doi:10.1177/0146621697211001>,
Adams, Wilson and Wu, 1997 <doi:10.3102/10769986022001047>,
Formann, 1982 <doi:10.1002/bimj.4710240209>,
Formann, 1992 <doi:10.1080/01621459.1992.10475229>.

Alexander Robitzsch

Test Analysis Modules

IRT.cv function

<dl> <dt>object</dt>
<dd>Object</dd><dt>...</dt>
<dd>Further arguments to be passed</dd></dl>

Arguments

Cross-Validation of a Fitted IRT Model — IRT.cv

<dl>

 <dt>object</dt>
<dd>Object</dd>

<dt>...</dt>
<dd>Further arguments to be passed</dd>

</dl>

IRT.cv: Cross-Validation of a Fitted IRT Model

Description

Usage

Value

Arguments