Description Usage Arguments Details Value Author(s) References Examples

View source: R/cronbach.alpha.R

Computes Cronbach's alpha for a given data-set.

1 2 |

`data` |
a |

`standardized` |
logical; if |

`CI` |
logical; if |

`probs` |
a numeric vector of length two indicating which quantiles to use for the Bootstrap CI. |

`B` |
the number of Bootstrap samples to use. |

`na.rm` |
logical; what to do with |

The Cronbach's alpha computed by `cronbach.alpha()`

is defined as follows

*alpha = (p / (p - 1)) (1 -
(∑_{i=1}^p sigma_{y_i}^2/ sigma_x^2)),*

where *p* is the number of items *sigma_x^2*
is the variance of the observed total test scores, and *sigma_{y_i}^2* is the variance
of the *i*th item.

The standardized Cronbach's alpha computed by `cronbach.alpha()`

is defined as follows

*alpha_s = (p r) / (1 + (p - 1) r),*

where *p* is the
number of items, and *r* is the average of all (Pearson) correlation coefficients between the
items. In this case if `na.rm = TRUE`

, then the complete observations (i.e., rows) are used.

The Bootstrap confidence interval is calculated by simply taking `B`

samples with replacement from `data`

,
calculating for each *alpha* or *alpha_s*, and computing the quantiles according to
`probs`

.

`cronbach.alpha()`

returns an object of class `cronbachAlpha`

with components

`alpha` |
the value of Cronbach's alpha. |

`n` |
the number of sample units. |

`p` |
the number of items. |

`standardized` |
a copy of the |

`name` |
the name of argument |

`ci` |
the confidence interval for alpha; returned if |

`probs` |
a copy of the |

`B` |
a copy of the |

Dimitris Rizopoulos [email protected]

Cronbach, L. J. (1951) Coefficient alpha and the internal structure of tests.
*Psychometrika*, **16**, 297–334.

1 2 3 | ```
# Cronbach's alpha for the LSAT data-set
# with a Bootstrap 95% CI
cronbach.alpha(LSAT, CI = TRUE, B = 500)
``` |

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