QIC | R Documentation |

Calculate quasi-likelihood under the independence model criterion (QIC) for Generalized Estimating Equations.

```
QIC(object, ..., typeR = FALSE)
QICu(object, ..., typeR = FALSE)
quasiLik(object, ...)
```

`object` |
a fitted model object of class |

`...` |
for QIC and QIC |

`typeR` |
logical, whether to calculate QIC(R). QIC(R) is
based on quasi-likelihood of a working correlation |

If just one object is provided, returns a numeric value with the
corresponding QIC; if more than one object are provided, returns a
`data.frame`

with rows corresponding to the objects and one column
representing QIC or QIC`_{u}`

.

This implementation is based partly on (revised) code from packages yags (R-Forge) and ape.

Kamil Bartoń

Pan, W. 2001 Akaike's Information Criterion in Generalized Estimating Equations.
*Biometrics* **57**, 120–125

Hardin J. W., Hilbe, J. M. 2003 *Generalized Estimating Equations*.
Chapman & Hall/CRC

Methods exist for
`gee`

(package gee),
`geeglm`

(geepack),
`geem`

(geeM),
`wgee`

(wgeesel, the package's `QIC.gee`

function is used),
and
`yags`

(yags on R-Forge).
There is also a `QIC`

function in packages MESS and geepack,
returning some extra information (such as CIC and QICc). `yags`

and
`compar.gee`

from package ape both provide QIC values.

```
data(ohio)
fm1 <- geeglm(resp ~ age * smoke, id = id, data = ohio,
family = binomial, corstr = "exchangeable", scale.fix = TRUE)
fm2 <- update(fm1, corstr = "ar1")
fm3 <- update(fm1, corstr = "unstructured")
# QIC function is also defined in 'geepack' but is returns a vector[6], so
# cannot be used as 'rank'. Either use `MuMIn::QIC` syntax or make a wrapper
# around `geepack::QIC`
QIC <- MuMIn::QIC
## Not run:
QIC <- function(x) geepack::QIC(x)[1]
## End(Not run)
model.sel(fm1, fm2, fm3, rank = QIC)
#####
library(geepack)
library(MuMIn)
## Not run:
# same result:
dredge(fm1, m.lim = c(3, NA), rank = QIC, varying = list(
corstr = list("exchangeable", "unstructured", "ar1")
))
## End(Not run)
```

MuMIn documentation built on March 31, 2023, 8:33 p.m.

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