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LSMjml  

Fitting Latent Space Item Response Models using Joint Maximum Likelihood Estimation
View on CRAN: Click here


Download and install LSMjml package within the R console
Install from CRAN:
install.packages("LSMjml")

Install from Github:
library("remotes")
install_github("cran/LSMjml")

Install by package version:
library("remotes")
install_version("LSMjml", "0.6.0")



Attach the package and use:
library("LSMjml")
Maintained by
Dylan Molenaar
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-12-19
Latest Update: 2025-12-19
Description:
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 (in press) 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.
How to cite:
Dylan Molenaar (2025). LSMjml: Fitting Latent Space Item Response Models using Joint Maximum Likelihood Estimation. R package version 0.6.0, https://cran.r-project.org/web/packages/LSMjml. Accessed 25 Oct. 2026.
Previous versions and publish date:
0.6.0 (2025-12-19 16:10), (2026-09-28 17:10)
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Complete documentation for LSMjml
Functions, R codes and Examples using the LSMjml R package
Full LSMjml package functions and examples
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