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QICW.gee

QICWr and QICWp for WGEE


Description

Calculate the QICWr and QICWp (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 QICWr, QICWp and Wquasi_lik.

Note

QICWr can be used for variable selection and for selecting the correlation structure in WGEE analyses. QICWp is a simplified version of QICWr, which can not be applied to select the optimal working correlation structure in WGEE.

Author(s)

Cong Xu, Zheng Li and Ming Wang

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

Examples

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)

wgeesel

Weighted Generalized Estimating Equations and Model Selection

v1.5
GPL-2
Authors
Cong Xu <congxu17@gmail.com>, Zheng Li <zheng.li@outlook.com>, Ming Wang <mwang@phs.psu.edu>
Initial release
2018-03-06

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