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# 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 <- charmatch(fnam, nam, 0)
if (any(wh == 0))
stop(paste("factor(s) not in design:", paste(names(factors)[wh == 0], 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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