Description Usage Arguments Value Note Author(s) References See Also Examples

Calculate quasi-likelihood under the independence model criterion (QIC) and QIC*u* based on GEE.

1 | ```
QIC.gee(object)
``` |

`object` |
a fitted model object of class |

Return a vector of QIC, QIC*u* and Quasi-likelihood.

QIC can be used to select the best correlation structure and the best fitting model in GEE analyses. The GEE is fitted by `geeglm`

(geepack). QIC*u* is a simplified version of QIC, which can not be applied to select the optimal working correlation structure. `geeglm`

(geepack) only works for complete data. Thus if there are NA’s in data, the missing values are automatically removed by `na.omit`

.

Cong Xu, Zheng Li and Ming Wang

Liang, K.Y. and Zeger, S.L., 1986. Longitudinal data analysis using generalized linear models. *Biometrika*, pp.13-22.

Pan, W., 2001. Akaike's information criterion in generalized estimating equations. *Biometrics*, 57(1), pp.120-125.

Prentice, R.L. and Zhao, L.P., 1991. Estimating equations for parameters in means and covariances of multivariate discrete and continuous responses. *Biometrics*, pp.825-839.

`geeglm`

(geepack). MuMIn also provides QIC value.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
data(imps)
fit <- wgee(Y ~ Drug+Sex+Time, data=imps, id=imps$ID, family="binomial",
corstr="exchangeable")
QIC.gee(fit)
data(seizure)
###reshapre the seizure data to "long" format
seiz.long <- reshape(seizure, varying=list(c("base","y1", "y2", "y3", "y4")),
v.names="y", times=0:4, direction="long")
seiz.long <- seiz.long[order(seiz.long$id, seiz.long$time),]
fit <- wgee(y ~ age + trt + time, data=seiz.long, id=seiz.long$id,
family="poisson", corstr="independence")
QIC.gee(fit)
``` |

```
QIC QICu Quasi_lik
1 1386.4 1380.5 -686.2
QIC QICu Quasi_lik
1 -12933 -12945.9 6476.9
```

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