The quasilikelihood information criterion (QIC) developed by Pan (2001) is a modification of the Akaike information criterion (AIC) for models fitted by GEE. `QIC`

is used for choosing the best correaltion structure and `QICu`

is used for choosing the best subset of covariates. The quasilikelihood (`QLike`

) is also reported for completeness. When choosing between two or more models, with different subset of covariates, the one with the smallest `QICu`

measure is preferred and similarly, when choosing between competing correlation structures, with the same subset of covariates in both, the model with the smallest `QIC`

measure is preferred.

1 | ```
QIC(object, digits = 3)
``` |

`object` |
is a fitted model using |

`digits` |
the number of decimal places to display in reported summaries. |

`QLike` |
model quasilikelihood. |

`QIC` |
model |

`QICu` |
model |

Pan W. Akaikes information criterion in generalized estimating equations. *Biometrics* 2001; 57:120-125.

1 2 3 4 5 6 |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.