lava (version 1.4.7)

twostage.lvmfit: Two-stage estimator (non-linear SEM)

Description

Two-stage estimator for non-linear structural equation models

Usage

"twostage"(object, model2, data = parent.frame(), predictfun = function(mu, var, data, ...) cbind(u1 = mu[, 1], u2 = mu[, 1]^2 + var[1]), id1, id2, all = FALSE, ...)

Arguments

object

Stage 1 measurement model

model2

Stage 2 SEM

data

data.frame

predictfun

Prediction of latent variable

id1

Optional id-variable (stage 1 model)

id2

Optional id-variable (stage 2 model)

all

If TRUE return additional output (naive estimates)

...

Additional arguments to lower level functions

Examples

m <- lvm(c(x1,x2,x3)~f1,f1~z,
         c(y1,y2,y3)~f2,f2~f1+z)
latent(m) <- ~f1+f2
d <- simulate(m,100,p=c("f2,f2"=2,"f1,f1"=0.5),seed=1)

## Full MLE
ee <- estimate(m,d)

## Manual two-stage
## Not run: 
# m1 <- lvm(c(x1,x2,x3)~f1,f1~z); latent(m1) <- ~f1
# e1 <- estimate(m1,d)
# pp1 <- predict(e1,f1~x1+x2+x3)
# 
# d$u1 <- pp1[,]
# d$u2 <- pp1[,]^2+attr(pp1,"cond.var")
# m2 <- lvm(c(y1,y2,y3)~eta,c(y1,eta)~u1+u2+z); latent(m2) <- ~eta
# e2 <- estimate(m2,d)
# ## End(Not run)

## Two-stage
m1 <- lvm(c(x1,x2,x3)~f1,f1~z); latent(m1) <- ~f1
m2 <- lvm(c(y1,y2,y3)~eta,c(y1,eta)~u1+u2+z); latent(m2) <- ~eta
pred <- function(mu,var,data,...)
    cbind("u1"=mu[,1],"u2"=mu[,1]^2+var[1])
(mm <- twostage(m1,model2=m2,data=d,predictfun=pred))

if (interactive()) {
    pf <- function(p) p["eta"]+p["eta~u1"]*u + p["eta~u2"]*u^2
    plot(mm,f=pf,data=data.frame(u=seq(-2,2,length.out=100)),lwd=2)
}