QIC: QIC for Generalized Estimating Equations

In glmtoolbox: Set of Tools to Data Analysis using Generalized Linear Models

QIC for Generalized Estimating Equations

Description

Computes the quasi-likelihood under the independence model criterion (QIC) for one or more objects of the class glmgee.

Usage

QIC(
  ...,
  k = 2,
  u = FALSE,
  verbose = TRUE,
  digits = max(3, getOption("digits") - 2)
)

Arguments

...	one or several objects of the class glmgee.
k	an (optional) non-negative value giving the magnitude of the penalty. As default, k is set to 2.
u	an (optional) logical switch indicating if QIC should be replaced by QICu. As default, u is set to FALSE.
verbose	an (optional) logical switch indicating if should the report of results be printed. As default, verbose is set to TRUE.
digits	an (optional) integer indicating the number of digits to print. As default, digits is set to max(3, getOption("digits") - 2).

Value

A data.frame with the values of -2*quasi-likelihood, the number of parameters in the linear predictor, and the value of QIC (or QICu if u=TRUE) for each glmgee object in the input.

References

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

Hin L.-Y., Carey V.J., Wang Y.-G. (2007) Criteria for Working–Correlation–Structure Selection in GEE: Assessment via Simulation. The American Statistician 61:360–364.

Vanegas L.H., Rondon L.M., Paula G.A. (2023) Generalized Estimating Equations using the new R package glmtoolbox. The R Journal 15:105-133.

See Also

CIC, GHYC, RJC, AGPC, SGPC

Examples

###### Example 1: Effect of ozone-enriched atmosphere on growth of sitka spruces
data(spruces)
mod1 <- size ~ poly(days,4) + treat
fit1 <- glmgee(mod1, id=tree, family=Gamma(log), data=spruces)
fit2 <- update(fit1, corstr="AR-M-dependent")
fit3 <- update(fit1, corstr="Stationary-M-dependent(2)")
fit4 <- update(fit1, corstr="Exchangeable")
QIC(fit1, fit2, fit3, fit4)

###### Example 2: Treatment for severe postnatal depression
data(depression)
mod2 <- depressd ~ visit + group
fit1 <- glmgee(mod2, id=subj, family=binomial(logit), data=depression)
fit2 <- update(fit1, corstr="AR-M-dependent")
fit3 <- update(fit1, corstr="Stationary-M-dependent(2)")
fit4 <- update(fit1, corstr="Exchangeable")
QIC(fit1, fit2, fit3, fit4)

###### Example 3: Treatment for severe postnatal depression (2)
mod3 <- dep ~ visit*group
fit1 <- glmgee(mod3, id=subj, family=gaussian(identity), data=depression)
fit2 <- update(fit1, corstr="AR-M-dependent")
fit3 <- update(fit1, corstr="Exchangeable")
QIC(fit1, fit2, fit3)

glmtoolbox documentation built on Sept. 11, 2024, 7:32 p.m.