dylanmolenaar-nl.r-universe.dev

[dylanmolenaar-nl] LSMjml 0.7.0

d.molenaar@uva.nl (Dylan Molenaar) — Mon, 28 Sep 2026 15:10:02 GMT

In Latent Space Item Response Models, subjects and items are embedded in a multidimensional Euclidean latent space. As such, interactions among persons, items, and person-item combinations can be revealed that are unmodelled in more conventional item response theory models. This package implements the methods from Molenaar & Jeon (2026) and can be used to fit Latent Space Item Response Models to data using joint maximum likelihood estimation. The package can handle binary data, ordinal data, and data with mixed scales. The package incorporates facilities for data simulation, rotation of the latent space, and K-fold cross-validation to select the number of dimensions of the latent space.

[dylanmolenaar-nl] BoundIRT 0.8.0

d.molenaar@uva.nl (Dylan Molenaar) — Wed, 16 Sep 2026 17:08:22 GMT

Bounded continuous data are encountered in many areas of test application. Examples include visual analogue scales used in the measurement of personality, mood, depression, and quality of life; item response times from tests with item deadlines; confidence ratings; and pain intensity ratings. Using this package, item response theory (IRT) models suitable for bounded continuous item scores can be fitted to data within a Bayesian framework. The package draws on posterior sampling facilities provided by R-package 'rstan' (Stan Development Team, 2025). Available models include the Beta IRT model by Noel and Dauvier (2007), the continuous response model by Samejima (1973), the unbounded normal model by Mellenbergh (1994), and the Simplex IRT model by Flores et al. (2020). All models can be fitted with or without zero-one inflation (Molenaar et al., 2022). Model fit comparisons can be conducted using the Watanabe-Akaike information criterion (WAIC), leave-one-out cross-validation information criterion (LOOIC), and the fully marginalized likelihood (i.e., Bayes factors).

[dylanmolenaar-nl] diffIRT 1.5

d.molenaar@uva.nl (Dylan Molenaar) — Thu, 13 Aug 2015 00:00:00 GMT

Package to fit diffusion-based IRT models to response and response time data. Models are fit using marginal maximum likelihood. Parameter restrictions (fixed value and equality constraints) are possible. In addition, factor scores (person drift rate and person boundary separation) can be estimated. Model fit assessment tools are also available. The traditional diffusion model can be estimated as well.