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### Support for emmeans package
#
# Note: the recover_data and emm_basis methods are registered dynamically
# (see zzz.R). So these functions are not exported
#' @importFrom utils getS3method
recover_data.lm_robust <- function(object, ...) {
data <- getS3method("recover_data", "lm")(object, ...)
if (object$rank < object$k) # rank-deficient. Need to pass dataset to emm_basis
attr(data, "pass.it.on") <- TRUE
data
}
emm_basis.lm_robust <- function(object, trms, xlev, grid, ...) {
# coef() works right for lm but coef.aov tosses out NAs
bhat <- coef(object)
n.mult <- ifelse(is.matrix(bhat), ncol(bhat), 1) # columns in mult response
m <- suppressWarnings(model.frame(trms, grid, na.action = na.pass, xlev = xlev))
X <- model.matrix(trms, m, contrasts.arg = object$contrasts)
V <- emmeans::.my.vcov(object, ...)
if (!anyNA(bhat))
nbasis <- estimability::all.estble
else {
desmat <- model.matrix(trms, data = attr(object, "data"))
nbasis <- estimability::nonest.basis(desmat)
}
misc <- list()
if (n.mult > 1) { # multivariate case. Need to expand some matrices
eye <- diag(n.mult)
X <- kronecker(eye, X)
nbasis <- kronecker(eye, nbasis)
if(is.null(colnames(bhat)))
colnames(bhat) <- seq_len(n.mult)
misc$ylevs <- list(rep.meas = colnames(bhat))
bhat <- as.numeric(bhat) # stretch coefs into a vector
}
dfargs <- list(df = object$df.residual)
dffun <- function(k, dfargs) dfargs$df
list(X = X, bhat = bhat, nbasis = nbasis, V = V,
dffun = dffun, dfargs = dfargs, misc = misc)
}
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