CompositeReliability: Determine the Composite Reliability of a Naturalistic, Unbalanced Dataset

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.

Version: 1.0.3
Depends: R (≥ 2.10)
Imports: dplyr, ggplot2, lme4, magrittr, plyr, psych, reshape2, tidyr, Rsolnp
Published: 2023-08-21
Author: Joyce Moonen - van Loon ORCID iD [aut, cre]
Maintainer: Joyce Moonen - van Loon <j.moonen at maastrichtuniversity.nl>
BugReports: https://github.com/jmoonen/CompositeReliability/issues
License: GPL (≥ 3)
URL: https://github.com/jmoonen/CompositeReliability
NeedsCompilation: no
Materials: README NEWS
CRAN checks: CompositeReliability results

Documentation:

Reference manual: CompositeReliability.pdf

Downloads:

Package source: CompositeReliability_1.0.3.tar.gz
Windows binaries: r-prerel: CompositeReliability_1.0.3.zip, r-release: CompositeReliability_1.0.3.zip, r-oldrel: CompositeReliability_1.0.3.zip
macOS binaries: r-prerel (arm64): CompositeReliability_1.0.3.tgz, r-release (arm64): CompositeReliability_1.0.3.tgz, r-oldrel (arm64): CompositeReliability_1.0.3.tgz, r-prerel (x86_64): CompositeReliability_1.0.3.tgz, r-release (x86_64): CompositeReliability_1.0.3.tgz
Old sources: CompositeReliability archive

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