Stack estimating equations — stack.estimate • lava

Stack estimating equations (two-stage estimator)

# S3 method for estimate
stack(
  x,
  model2,
  D1u,
  inv.D2u,
  propensity,
  dpropensity,
  U,
  keep1 = FALSE,
  propensity.arg,
  estimate.arg,
  na.action = na.pass,
  ...
)

Arguments

x: Model 1
model2: Model 2
D1u: Derivative of score of model 2 w.r.t. parameter vector of model 1
inv.D2u: Inverse of deri
propensity: propensity score (vector or function)
dpropensity: derivative of propensity score wrt parameters of model 1
U: Optional score function (model 2) as function of all parameters
keep1: If FALSE only parameters of model 2 is returned
propensity.arg: Arguments to propensity function
estimate.arg: Arguments to 'estimate'
na.action: Method for dealing with missing data in propensity score
...: Additional arguments to lower level functions

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))
#>             Estimate Std.Err   2.5% 97.5%   P-value
#> (Intercept)   0.9076 0.08836 0.7344 1.081 9.454e-25