hlt
1.3.1Higher-Order Item Response Theory
Overview
Higher-order latent trait theory (item response theory). We implement the generalized partial credit model with a second-order latent trait structure. Latent regression can be done on the second-order latent trait. For a pre-print of the methods, see, "Latent Regression in Higher-Order Item Response Theory with the R Package hlt" https://mkleinsa.github.io/doc/hlt_proof_draft_brmic.pdf.
Install
Health
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- NOTE2026-04-220 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-180 OK · 13 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-04-100 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-090 OK · 13 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-100 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 92%
- Return-value docs
- 100%
- References docs
- 20%
Downloads
Repository
Repository practices
Repository github.com/mkleinsa/hlt is linked, but repository-practices checks have not run for it yet.
Dependencies
Code & Tests
Datasets
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.3.1Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2022-08-22
- Total releases
- 1 / 4 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 14 KB / 1 file
- Download size
- 3.0 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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