computeCompositeReliability {CompositeReliability} | R Documentation |

## 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
```

[Package

*CompositeReliability*version 1.0.3 Index]