BIC.rma <- function(object, ...) {
mstyle <- .get.mstyle()
.chkclass(class(object), must="rma")
if (missing(...)) {
### if there is just 'object'
if (object$method == "REML") {
out <- object$fit.stats["BIC","REML"]
} else {
out <- object$fit.stats["BIC","ML"]
}
} else {
### if there is 'object' and additional objects via ...
if (object$method == "REML") {
out <- sapply(list(object, ...), function(x) x$fit.stats["BIC","REML"])
} else {
out <- sapply(list(object, ...), function(x) x$fit.stats["BIC","ML"])
}
dfs <- sapply(list(object, ...), function(x) x$parms)
out <- data.frame(df=dfs, BIC=out)
### get names of objects; same idea as in stats:::AIC.default
cl <- match.call()
rownames(out) <- as.character(cl[-1L])
### check that all models were fitted to the same data
yis <- lapply(list(object, ...), function(x) as.vector(x$yi))
if (!all(sapply(yis[-1], function(x) identical(x, yis[[1]]))))
warning(mstyle$warning("Models not all fitted to the same data."), call.=FALSE)
}
return(out)
}
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