Description Usage Arguments Details Value

Extract or compute the (expected) second derivative of the log-likelihood of a linear mixed model.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 |

`x` |
a |

`effects` |
[character] Should the information relative to all coefficients be output ( |

`data` |
[data.frame] dataset relative to which the information should be computed. Only relevant if differs from the dataset used to fit the model. |

`p` |
[numeric vector] value of the model coefficients at which to evaluate the information. Only relevant if differs from the fitted values. |

`indiv` |
[logical] Should the contribution of each cluster to the information be output? Otherwise output the sum of all clusters of the derivatives. |

`type.information` |
[character] Should the expected information be computed (i.e. minus the expected second derivative) or the observed inforamtion (i.e. minus the second derivative). |

`transform.sigma` |
[character] Transformation used on the variance coefficient for the reference level. One of |

`transform.k` |
[character] Transformation used on the variance coefficients relative to the other levels. One of |

`transform.rho` |
[character] Transformation used on the correlation coefficients. One of |

`transform.names` |
[logical] Should the name of the coefficients be updated to reflect the transformation that has been used? |

`...` |
Not used. For compatibility with the generic method. |

For details about the arguments **transform.sigma**, **transform.k**, **transform.rho**, see the documentation of the coef function.

When argument indiv is `FALSE`

, a matrix with the value of the infroamtion relative to each pair of coefficient (in rows and columns) and each cluster (in rows).
When argument indiv is `TRUE`

, a 3-dimensional array with the value of the information relative to each pair of coefficient (dimension 2 and 3) and each cluster (dimension 1).

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