isni (version 0.1)

isnigls: Function for ISNI computation when the outcome follows GLS.

Description

Calculate the ISNI when the regression outcome is subject to missingness and follows generalized linear models (GLMs)

Usage

isnigls(ymodel, gmodel, ycorr = "CS", predprobobs = NULL, misni = FALSE,
  alldata)

Arguments

ymodel

an object of class "formula": a symbolic description of the model to be fitted for the outcome

gmodel

an object of class "formula": a symbolic description of the selection model to be fitted for the missingness indictor g

ycorr

the form of within-subject correlation structure.

predprobobs

Null if using buil-in multinomial transitional logistic model to obtain predicted probabilities of being observed; otherwise user supply a vector of these probabilities for all the observations in alldata.

misni

FALSE if using the default approach to computing ISNI with a scalar nonignorability parameter; TRUE when computing ISNI with multiple nonignorability parameters.

alldata

the name of data frame containing all the variables in the model and all the observations including those intended to be collected but became missing.

Examples

# NOT RUN {
ymodel= y~   t1+t3+t6 + group  + t12 + t32+t62 + perf + sever
gmodel= as.factor(g)~ t3+t6+group+yp+perf+sever
qolef$t12<-qolef$t1*qolef$group
qolef$t32<-qolef$t3*qolef$group
qolef$t62<-qolef$t6*qolef$group

qolef.isni=isnigls(ymode=ymodel, gmodel=gmodel, alldata=qolef)
summary(qolef.isni)

# }