wgeesel (version 1.5)

QICW.gee: QICWr and QICWp for WGEE

Description

Calculate the QICW\(_{r}\) and QICW\(_{p}\) (an information criterion based on the weighted quasi-likelihood function) for selection of mean model and correlation structure based on the WGEE.

Usage

QICW.gee(object)

Arguments

object

a fitted model object of class "wgee".

Value

Return a data frame of QICW\(_{r}\), QICW\(_{p}\) and Wquasi_lik.

References

Gosho, M., 2015. Model selection in the weighted generalized estimating equations for longitudinal data with dropout. Biometrical Journal.

Platt, R.W., Brookhart, M.A., Cole, S.R., Westreich, D. and Schisterman, E.F., 2013. An information criterion for marginal structural models. Statistics in medicine, 32(8), pp.1383-1393.

Robins, J.M., Rotnitzky, A. and Zhao, L.P., 1995. Analysis of semiparametric regression models for repeated outcomes in the presence of missing data. Journal of the American Statistical Association, 90(429), pp.106-121.

See Also

wgee

Examples

# NOT RUN {
data(imps)

### variable selection by QICWr, not rum###
#fit <- wgee(IMPS79 ~ Drug+Sex+Time, mismodel= R ~ Drug+Time, data=imps,
##           id=imps$ID, family="gaussian", corstr="exchangeable")
##QICW.gee(fit)

#fit <- wgee(IMPS79 ~ Drug+Sex+Time+Time:Sex+Time:Drug, mismodel= R ~ Drug+Time,
#        data=imps, id=imps$ID, family="gaussian", corstr="exchangeable")
##QICW.gee(fit)
# }