Nothing
factor.scores.grm <-
function (object, resp.patterns = NULL, method = c("EB", "EAP", "MI"), B = 5,
prior = TRUE, return.MIvalues = FALSE, ...) {
if (!inherits(object, "grm"))
stop("Use only with 'grm' objects.\n")
betas <- object$coefficients
fits <- fitted(object, resp.patterns = resp.patterns)
X <- fits[, -ncol(fits), drop = FALSE]
nx <- nrow(X)
p <- length(betas)
method <- match.arg(method)
if (method == "MI" && is.null(object$hessian)) {
warning("object does not have an estimate of the Hessian; the 'EB' method is used instead.\n")
method <- "EB"
}
Obs <- observedFreqs(object, X)
res <- data.frame(X, Obs = Obs, Exp = fits[, ncol(fits)])
names(res)[1:p] <- names(betas)
environment(fscores.g) <- environment()
res <- fscores.g(betas, X, method)
out <- list(score.dat = res, method = method, B = B, call = object$call, resp.pats = !is.null(resp.patterns))
class(out) <- "fscores"
out
}
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