# QIC: QIC and quasi-Likelihood for GEE In MuMIn: Multi-Model Inference

 QIC R Documentation

## QIC and quasi-Likelihood for GEE

### Description

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

### Usage

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

### Arguments

 `object` a fitted model object of class `"gee"`, `"geepack"`, `"geem"`, `"wgee"`, or `"yags"`. `...` for QIC and QIC`_{u}`, optionally more fitted model objects. `typeR` logical, whether to calculate QIC(R). QIC(R) is based on quasi-likelihood of a working correlation `R` model. Defaults to `FALSE`, and QIC(I) based on independence model is returned.

### Value

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}`.

### Note

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

Kamil Bartoń

### References

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.

### Examples

``````

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.