SAS PROC IRT and the R mirt Package: A Comparison of Model Parameter Estimation for Multidimensional IRT Models

LIRT: SAS macros for longitudinal IRT models

Item response theory models are often applied when a number items are used to measure a unidimensional latent variable. Originally proposed within educational research, they are now also being used when focus is on e.g. physical functioning or psychological well-being. Modern applications often need more general models, typically models for multidimensional latent variables or longitudinal mode...

The Added Value of Multidimensional IRT Models

IRT-FIT: SAS® Macros for Fitting Item Response Theory (IRT) Models

Psychometrics has recently seen the development of complex measurement models to better represent test and item data. Item Response Theory (IRT), in particular, comprises a set of non-linear latent variable models that appear to have several conceptual and empirical properties that make them more valuable in practice than classical test theory methods. However, IRT-based models typically requir...

IRT Observed-Score Kernel Equating with the R Package kequate

The R package kequate enables observed-score equating using the kernel method of test equating. We present the recent developments of kequate, which provide additional support for item-response theory observed score equating using 2-PL and 3-PL models in the equivalent groups design and non-equivalent groups with anchor test design using chain equating. The implementation also allows for local ...

Bayesian Multidimensional IRT Models With a Hierarchical Structure

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