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 |
DOI: |
10.32614/CRAN.package.CompositeReliability |
Author: |
Joyce Moonen - van Loon
[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:
Downloads:
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