Parameter Estimation of Item Response Theory with Estimation of Latent Distribution
Overview
Item response theory (IRT) parameter estimation using marginal maximum likelihood and expectation-maximization algorithm (Bock \& Aitkin, 1981 doi:10.1007/BF02293801). Within parameter estimation algorithm, several methods for latent distribution estimation are available. Reflecting some features of the true latent distribution, these latent distribution estimation methods can possibly enhance the estimation accuracy and free the normality assumption on the latent distribution.
- Discretized response analysis is partially supported;
dr1assumes equal intervals and estimates the slope, intercept, and precision parameters, anddr2uses fixed slope and intercept parameters and estimates the category intervals.
From NEWS.md in the release
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- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 26
- Examples that run
- 12%2 run in a plain check · 15 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 68%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 35%
Downloads
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- PRs merged (all time)
- 71%
- Median days to close, 50 most recently updated closed issues
- 1
- Median days to close, 50 most recently updated closed PRs
- 0
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- RR 4.6.0 released · 2026-04-24
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- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-09-06
- Total releases
- 9 / 4 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5
- Download size
- 334 KB
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