RJC {glmtoolbox} | R Documentation |
Rotnitzky–Jewell's Criterion for Generalized Estimating Equations
Description
Computes the Rotnitzky–Jewell's criterion (RJC) for one or more objects of the class glmgee.
Usage
RJC(..., 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, |
digits |
an (optional) integer indicating the number of digits to print. As default, |
Value
A data.frame
with the values of the RJC for each glmgee object in the input.
References
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.
See Also
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")
RJC(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")
RJC(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")
RJC(fit1, fit2, fit3)
[Package glmtoolbox version 0.1.12 Index]