Nothing
# generic functions defined in rms
#
# contrast <- function(fit, ...) UseMethod("contrast")
# gendata <- function(fit, ...) UseMethod("gendata")
# this overrides the version in nlme which doesn't work for us
formula.gls <- function(x, ..., env = NULL) {
if (is.null(env)) {
# this seems silly, but it's the way gls defines formula
eval(x$call$model)
} else {
# this gives you some control if you know what you're doing
eval(x$call$model, env)
}
}
# methods neeeded, but missing, from geepack
coef.geese <- function(object, ...) object$beta
vcov.geese <- function(object, ...) object$vbeta
# This function mimics rms:::gendata, which is unusable
# on non-rms objects
generateData <- function(fit, factors, ..., env = NULL) {
tt <- tryCatch(
terms(fit),
error = function(e) {
terms(formula(fit, env = env))
}
)
order <- attr(tt, "order")
tlabs <- attr(tt, "term.labels")
nam <- tlabs[order == 1]
fnam <- names(factors)
nf <- length(factors)
if (nf == 0) {
stop("illegal factors argument")
}
wh <- sapply(fnam, function(x) any(grepl(x, nam, fixed = TRUE)))
if (!all(wh)) {
stop(paste(
"factor(s) not in design:",
paste(names(factors)[!wh], collapse = " ")
))
}
if (nf < length(nam)) {
stop("not enough factors")
}
settings <- list()
for (i in 1:nf) {
settings[[fnam[i]]] <- factors[[i]]
}
expand.grid(settings)
}
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