Nothing
anova.mclogit <- function (object, ..., dispersion = NULL, test = NULL)
{
dotargs <- list(...)
named <- if (is.null(names(dotargs)))
rep_len(FALSE, length(dotargs))
else (names(dotargs) != "")
if (any(named))
warning("the following arguments to 'anova.mclogit' are invalid and dropped: ",
paste(deparse(dotargs[named]), collapse = ", "))
dotargs <- dotargs[!named]
is.mclogit <- vapply(dotargs, function(x) inherits(x, "mclogit") ,
#&!inherits(x,"mclogitRandeff"),
NA)
dotargs <- dotargs[is.mclogit]
if (length(dotargs))
return(anova.mclogitlist(c(list(object), dotargs), dispersion = dispersion,
test = test))
stop("'anova.mclogit' can only be used to compare fitted models")
}
anova.mclogitlist <- function (object, ..., dispersion = NULL, test = NULL)
{
responses <- as.character(lapply(object, function(x) {
deparse(formula(x)[[2L]])
}))
sameresp <- responses == responses[1L]
if (!all(sameresp)) {
object <- object[sameresp]
warning(gettextf("models with response %s removed because response differs from model 1",
sQuote(deparse(responses[!sameresp]))), domain = NA)
}
ns <- sapply(object, function(x) x$N)
if (any(ns != ns[1L]))
stop("models were not all fitted to the same size of dataset")
nmodels <- length(object)
if (nmodels == 1) stop("'anova.mclogit' can only be used to compare fitted models")
hasRE <- sapply(object,inherits,"mmclogit")
if(any(hasRE)) warning("Results are unreliable, since deviances from quasi-likelihoods are not comparable.")
resdf <- as.numeric(lapply(object, function(x) x$df.residual))
resdev <- as.numeric(lapply(object, function(x) x$deviance))
table <- data.frame(resdf, resdev, c(NA, -diff(resdf)), c(NA,
-diff(resdev)))
variables <- lapply(object, function(x) paste(deparse(formula(x)),
collapse = "\n"))
dimnames(table) <- list(1L:nmodels, c("Resid. Df", "Resid. Dev",
"Df", "Deviance"))
title <- "Analysis of Deviance Table\n"
topnote <- paste("Model ", format(1L:nmodels), ": ", variables,
sep = "", collapse = "\n")
if (!is.null(test)) {
bigmodel <- object[[order(resdf)[1L]]]
df.dispersion <- Inf
table <- stat.anova(table = table, test = test, scale = 1,
df.scale = df.dispersion, n = bigmodel$N)
}
structure(table, heading = c(title, topnote), class = c("anova",
"data.frame"))
}
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