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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/stack.R
\name{stack.estimate}
\alias{stack.estimate}
\title{Stack estimating equations}
\usage{
\method{stack}{estimate}(
x,
model2,
D1u,
inv.D2u,
propensity,
dpropensity,
U,
keep1 = FALSE,
propensity.arg,
estimate.arg,
na.action = na.pass,
...
)
}
\arguments{
\item{x}{Model 1}
\item{model2}{Model 2}
\item{D1u}{Derivative of score of model 2 w.r.t. parameter vector of model 1}
\item{inv.D2u}{Inverse of deri}
\item{propensity}{propensity score (vector or function)}
\item{dpropensity}{derivative of propensity score wrt parameters of model 1}
\item{U}{Optional score function (model 2) as function of all parameters}
\item{keep1}{If FALSE only parameters of model 2 is returned}
\item{propensity.arg}{Arguments to propensity function}
\item{estimate.arg}{Arguments to 'estimate'}
\item{na.action}{Method for dealing with missing data in propensity score}
\item{...}{Additional arguments to lower level functions}
}
\description{
Stack estimating equations (two-stage estimator)
}
\examples{
m <- lvm(z0~x)
Missing(m, z ~ z0) <- r~x
distribution(m,~x) <- binomial.lvm()
p <- c(r=-1,'r~x'=0.5,'z0~x'=2)
beta <- p[3]/2
d <- sim(m,500,p=p,seed=1)
m1 <- estimate(r~x,data=d,family=binomial)
d$w <- d$r/predict(m1,type="response")
m2 <- estimate(z~1, weights=w, data=d)
(e <- stack(m1,m2,propensity=TRUE))
}
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