Using clustered covariance matrix in predict.lm()

Question

I am analyzing a dataset in which data is clustered in several groups (towns in regions). The dataset looks like:

R> df <- data.frame(x = rnorm(10), 
             


        

Answer 1

I modified the above code slightly to be more consistent with the predict function--this way you are not expected to enter values for the outcome in the newdata dataframe

predict.rob <- function(x,clcov,newdata){
if(missing(newdata)){ newdata <- x$model }
tt <- terms(x)
Terms <- delete.response(tt)
m.mat <- model.matrix(Terms,data=newdata)
m.coef <- x$coef
fit <- as.vector(m.mat %*% x$coef)
se.fit <- sqrt(diag(m.mat%*%clcov%*%t(m.mat)))
return(list(fit=fit,se.fit=se.fit))}