Determine the Composite Reliability of a Naturalistic, Unbalanced Dataset
calculateReliability: determine the reliability and SEM per Type
calculateVarCov: Estimate variance and covariance components of assess...
checkDatasets: assert that the given datasets adhere to the assumption...
computeCompositeReliability: multivariate generalizability theory appr...
computeMaxCompositeReliability: multivariate generalizability theory a...
DStudy: the program presents the reliability coefficient and the SEM f...
GStudy for a dataset in which every student p has a potentially differ...
GStudyPerType: This function is mainly used within calculateVarCov.R, ...
Pipe operator
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.
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