Nothing
## bootstrap standard errors for aggregated effects
## not yet ready to use!
elrCondeffectsBoot <- function(data, m1, formula, nboot=1000, est="lm", se="boot"){
if(is.na(nboot)){
d <- cbind(m1@results@condeffects, data)
Estimates <- coef(lm(formula, data=d))
res <- data.frame(Estimates, SE=as.numeric(NA))
}else{
bootsamples <- elr_condeff_boot_samples(data, m1, formula, nboot)
if(est=="lm"){
d <- cbind(m1@results@condeffects, data)
Estimates <- coef(lm(formula, data=d))
}else if(est=="boot"){
Estimates <- colMeans(bootsamples, na.rm=TRUE)
}
SE <- apply(bootsamples, 2, function(x){sd(x, na.rm=TRUE)})
res <- data.frame(Estimates,SE)
}
return(res)
}
## generate the bootstrap samples and return all results
elr_condeff_boot_samples <- function(data, m1, formula, nboot){
N <- nrow(data)
call <- m1@call
call$data <- quote(dboot)
res <- vector("list", length=nboot)
for(i in 1:nboot){
idx <- sample(1:N, size=N, replace=TRUE)
dboot <- data[idx,]
mboot <- try(eval(call))
if(inherits(mboot, "try-error")){
res[[i]] <- NA
}else{
condeffects <- mboot@results@condeffects
dboot <- cbind(condeffects, dboot)
m1.lm <- lm(formula, data=dboot)
res[[i]] <- coef(m1.lm)
}
}
res <- as.data.frame(do.call(rbind, res))
return(res)
}
# test <- elrCondeffectsBoot(data=example01,m1=m1,formula=g1~z1,nboot=2)
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