computeCompositeReliability {CompositeReliability}

computeCompositeReliability: multivariate generalizability theory approach to estimate the composite reliability of student performance across different types of assessments.

Description

computeCompositeReliability: multivariate generalizability theory approach to estimate the composite reliability of student performance across different types of assessments.

Usage

computeCompositeReliability(mydata, n, weights, optimizeSEM)

Arguments

mydata

A dataframe containing columns ID, Type, Score (numeric)

n

A vector containing for each Type the number of score or assessments assessments, e.g. averages, requirements.

weights

A vector containing for each Type the weight assigned to it. The sum of weights should be equal to 1.

optimizeSEM

Boolean, if TRUE, the weights are adjusted in order to minimize the Standard Error of Measurement (SEM)

Value

A list containing the composite reliability coefficient, the SEM and the distribution of weights. If 'optimizeSEM' is set to TRUE, the vector of weights minimizes the SEM.

Examples

compRel <- computeCompositeReliability(mydata, n=c("A"=10, "B"=5, "C"=2),
                            weights=c("A"=1/3,"B"=1/3, "C"=1/3), optimizeSEM=TRUE)
compRel$reliability
compRel$SEM
compRel$weights