R: Stack estimating equations

stack.estimate {lava} | R Documentation

## Stack estimating equations

### Description

Stack estimating equations (two-stage estimator)

### Usage

    ## S3 method for class '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)
    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))

[Package lava version 1.6.1 Index]