calculateVarCov

calculateVarCov: Estimate variance and covariance components of assessee p S_p and mean assessment scores i nested in assessees S_iINp,
and determine the error scores S_delta

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 in nested design as is often the case for Workplace-Based Assessments. This package is designed to estimate composite reliability in nested designs using multivariate generalizability theory and enhance the analysis of assessment data. The package allows for the inclusion of weight per assessment type and produces extensive G- and D-study results with graphical interpretations, and options to find the set of weights that maximizes the composite reliability or minimizes the standard error of measurement (SEM).

Joyce Moonen - van Loon

compositeReliabilityInNestedDesigns

Optimizing the Composite Reliability in Multivariate Nested
Designs

calculateVarCov function

<dl><dt>mydata</dt>
<dd>A dataframe containing columns ID, Type, Score (numeric)</dd>
<dt>n</dt>
<dd>A vector containing for each Type the number of scores or assessments, e.g. averages, requirements.</dd></dl>

Arguments

calculateVarCov: Estimate variance and covariance components of assessee p S_p and mean assessment scores i nested in assessees S_iINp,
and determine the error scores S_delta — calculateVarCov

<dl>

<dt>mydata</dt>
<dd>A dataframe containing columns ID, Type, Score (numeric)</dd>


<dt>n</dt>
<dd>A vector containing for each Type the number of scores or assessments, e.g. averages, requirements.</dd>

</dl>

calculateVarCov: Estimate variance and covariance components of assessee p S_p and mean assessment scores i nested in assessees S_iINp,
and determine the error scores S_delta

calculateVarCov: calculateVarCov: Estimate variance and covariance components of assessee p S_p and mean assessment scores i nested in assessees S_iINp, and determine the error scores S_delta

Description

Usage

Value

Arguments

Examples