Determine the Composite Reliability of a Naturalistic, Unbalanced Dataset
Overview
The reliability of assessment tools is a crucial aspect of monitoring student performance in various educational settings. It ensures that the assessment outcomes accurately reflect a student's true level of performance. However, when assessments are combined, determining composite reliability can be challenging, especially for naturalistic and unbalanced datasets. This package provides an easy-to-use solution for calculating composite reliability for different assessment types. It allows for the inclusion of weight per assessment type and produces extensive G- and D-study results with graphical interpretations. Overall, our approach enhances the reliability of composite assessments, making it suitable for various education contexts.
- Included function computeMaxCompositeReliability to maximize the Composite Reliability Coefficient for a given set numbers of assessment types
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 10 (1 internal)
- Examples that run
- 86%6 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 78%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
Moved from jmoonen/compositereliability.
2 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/jmoonen/compositereliability on 2026-10-21.
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.0.3Latest
- 1.0.22023-07-21
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2023-07-21
- Total releases
- 2 / 3 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 0.3 KB / 1 file
- Download size
- 8.7 KB
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