QICmiipw {MIIPW} | R Documentation |
Model Selection criteria QIC
Description
It provides model selection criteria such as quasi-likelihood under the independence model criterion (QIC), an approximation to QIC under large sample i.e QICu and quasi likelihood
Usage
QICmiipw(model.R, model.indep, family)
Arguments
model.R |
fitted object obtained from GEE model |
model.indep |
same fitted object as in |
family |
currently we have inlcuded "poisson","binomial","gaussian" |
Details
QICmiipw
Value
returns a list containing QIC,QICu,Quasi likelihood
References
Pan, Wei. "Akaike's information criterion in generalized estimating equations." Biometrics 57.1 (2001): 120-125.
Examples
## Not run:
##
formula<-C6kine~ActivinRIB+ActivinRIIA+ActivinRIIAB+Adiponectin+AgRP+ALCAM
pMat<-mice::make.predictorMatrix(srdata1[names(srdata1)%in%all.vars(formula)])
m1<-MeanScore(data=srdata1,
formula<-formula,id='ID',
visit='Visit',family='gaussian',init.beta = NULL,
init.alpha=NULL,init.phi=1,tol=.00001,weights = NULL,
corstr = 'exchangeable',maxit=50,m=2,pMat=pMat)
m11<-MeanScore(data=srdata1,
formula<-formula,id='ID',
visit='Visit',family='gaussian',init.beta = NULL,
init.alpha=NULL,init.phi=1,tol=.00001,weights = NULL,
corstr = 'independent',maxit=50,m=2,pMat=pMat)
QICmiipw(model.R=m1,model.indep=m11,family="gaussian")
##
## End(Not run)
[Package MIIPW version 0.1.1 Index]