# Quasilikelihood Information Criterion

### Description

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.

### Usage

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

### Arguments

`object` |
is a fitted model using |

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

### Value

`QLike` |
model quasilikelihood. |

`QIC` |
model |

`QICu` |
model |

### References

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

### Examples

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