GHYC {glmtoolbox}

Gosho-Hamada-Yoshimura's Criterion for Generalized Estimating Equations

Description

Computes the Gosho-Hamada-Yoshimura's criterion (GHYC) for one or more objects of the class glmgee.

Usage

GHYC(..., verbose = TRUE, digits = max(3, getOption("digits") - 2))

Arguments

...

one or several objects of the class glmgee.

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 the GHYC for each glmgee object in the input.

References

Gosho M., Hamada C., Yoshimura I. (2011) Criterion for the Selection of a Working Correlation Structure in the Generalized Estimating Equation Approach for Longitudinal Balanced Data. Communications in Statistics — Theory and Methods 40:3839-3856.

Gosho M. (2014) Criteria to Select a Working Correlation Structure in SAS. Journal of Statistical Software, Code Snippets 57:1548-7660.#' @references 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

QIC, CIC, 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")
GHYC(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")
GHYC(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")
GHYC(fit1, fit2, fit3)