Fitting Latent Space Item Response Models using Joint Maximum Likelihood Estimation
Overview
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)doi:10.1017/psy.2025.10068 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.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK12 OK2026-04-25
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- NOTE12 OK, 2 NOTE2026-04-22
- ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 6
- Examples that run
- 100%6 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 67%
Downloads
Dependencies
Installing LSMjml adds 10 packages (6 with compiled code, 7.9 MB of source tarballs). Heaviest: Rcpp 1.8 MB, GPArotation 1.6 MB, lavaan 1.6 MB.
Code & Tests
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- 0.7.0Latest
- RR 4.6.0 released · 2026-04-24
- 0.6.02025-12-19
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-12-19
- Total releases
- 2 / 1 yrs
- License
- GPL-3 OSI
- Download size
- 27 KB
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