cumul.rma.peto <- function(x, order, digits, transf, targs, collapse=FALSE, progbar=FALSE, ...) {
mstyle <- .get.mstyle()
.chkclass(class(x), must="rma.peto")
na.act <- getOption("na.action")
if (!is.element(na.act, c("na.omit", "na.exclude", "na.fail", "na.pass")))
stop(mstyle$stop("Unknown 'na.action' specified under options()."))
if (na.act == "na.fail" && any(!x$not.na))
stop(mstyle$stop("Missing values in data."))
if (missing(digits)) {
digits <- .get.digits(xdigits=x$digits, dmiss=TRUE)
} else {
digits <- .get.digits(digits=digits, xdigits=x$digits, dmiss=FALSE)
}
if (missing(transf))
transf <- FALSE
if (missing(targs))
targs <- NULL
ddd <- list(...)
.chkdots(ddd, c("time", "decreasing"))
if (.isTRUE(ddd$time))
time.start <- proc.time()
decreasing <- .chkddd(ddd$decreasing, FALSE)
#########################################################################
if (grepl("^order\\(", deparse1(substitute(order))))
warning(mstyle$warning("Use of order() in the 'order' argument is probably erroneous."), call.=FALSE)
if (missing(order)) {
orvar <- seq_len(x$k.all)
collapse <- FALSE
} else {
mf <- match.call()
orvar <- .getx("order", mf=mf, data=x$data)
if (length(orvar) != x$k.all)
stop(mstyle$stop(paste0("Length of the 'order' argument (", length(orvar), ") does not correspond to the size of the original dataset (", x$k.all, ").")))
}
### note: order variable must be of the same length as the original dataset
### so apply the same subsetting as was done during the model fitting
orvar <- .getsubset(orvar, x$subset)
### order data by the order variable (NAs in order variable are dropped)
order <- base::order(orvar, decreasing=decreasing, na.last=NA)
ai <- x$outdat.f$ai[order]
bi <- x$outdat.f$bi[order]
ci <- x$outdat.f$ci[order]
di <- x$outdat.f$di[order]
yi <- x$yi.f[order]
vi <- x$vi.f[order]
not.na <- x$not.na[order]
slab <- x$slab[order]
ids <- x$ids[order]
orvar <- orvar[order]
if (inherits(x$data, "environment")) {
data <- NULL
} else {
data <- x$data[order,]
}
if (collapse) {
uorvar <- unique(orvar)
} else {
uorvar <- orvar
}
k.o <- length(uorvar)
k <- rep(NA_integer_, k.o)
beta <- rep(NA_real_, k.o)
se <- rep(NA_real_, k.o)
zval <- rep(NA_real_, k.o)
pval <- rep(NA_real_, k.o)
ci.lb <- rep(NA_real_, k.o)
ci.ub <- rep(NA_real_, k.o)
QE <- rep(NA_real_, k.o)
QEp <- rep(NA_real_, k.o)
I2 <- rep(NA_real_, k.o)
H2 <- rep(NA_real_, k.o)
show <- rep(TRUE, k.o)
### elements that need to be returned
outlist <- "k=k, beta=beta, se=se, zval=zval, pval=pval, ci.lb=ci.lb, ci.ub=ci.ub, QE=QE, QEp=QEp, I2=I2, H2=H2"
if (progbar)
pbar <- pbapply::startpb(min=0, max=k.o)
for (i in seq_len(k.o)) {
if (progbar)
pbapply::setpb(pbar, i)
if (collapse) {
if (all(!not.na[is.element(orvar, uorvar[i])])) {
if (na.act == "na.omit")
show[i] <- FALSE # if all studies to be added are !not.na, don't show (but a fit failure is still shown)
next
}
incl <- is.element(orvar, uorvar[1:i])
} else {
if (!not.na[i]) {
if (na.act == "na.omit")
show[i] <- FALSE # if study to be added is !not.na, don't show (but a fit failure is still shown)
next
}
incl <- 1:i
}
args <- list(ai=ai, bi=bi, ci=ci, di=di, add=x$add, to=x$to, drop00=x$drop00, level=x$level, subset=incl, outlist=outlist)
res <- try(suppressWarnings(.do.call(rma.peto, args)), silent=TRUE)
if (inherits(res, "try-error"))
next
k[i] <- res$k
beta[i] <- res$beta
se[i] <- res$se
zval[i] <- res$zval
pval[i] <- res$pval
ci.lb[i] <- res$ci.lb
ci.ub[i] <- res$ci.ub
QE[i] <- res$QE
QEp[i] <- res$QEp
I2[i] <- res$I2
H2[i] <- res$H2
}
if (progbar)
pbapply::closepb(pbar)
#########################################################################
### if requested, apply transformation function
if (.isTRUE(transf)) # if transf=TRUE, apply exp transformation to ORs
transf <- exp
if (is.function(transf)) {
if (is.null(targs)) {
beta <- sapply(beta, transf)
se <- rep(NA_real_, k.o)
ci.lb <- sapply(ci.lb, transf)
ci.ub <- sapply(ci.ub, transf)
} else {
beta <- sapply(beta, transf, targs)
se <- rep(NA_real_, k.o)
ci.lb <- sapply(ci.lb, transf, targs)
ci.ub <- sapply(ci.ub, transf, targs)
}
transf <- TRUE
}
### make sure order of intervals is always increasing
tmp <- .psort(ci.lb, ci.ub)
ci.lb <- tmp[,1]
ci.ub <- tmp[,2]
#########################################################################
out <- list(k=k[show], estimate=beta[show], se=se[show], zval=zval[show], pval=pval[show], ci.lb=ci.lb[show], ci.ub=ci.ub[show], Q=QE[show], Qp=QEp[show], I2=I2[show], H2=H2[show])
if (collapse) {
out$slab <- uorvar[show]
out$slab.null <- FALSE
} else {
out$slab <- slab[show]
out$ids <- ids[show]
out$data <- data[show,,drop=FALSE]
out$slab.null <- x$slab.null
}
out$order <- uorvar[show]
out$digits <- digits
out$transf <- transf
out$level <- x$level
out$test <- x$test
if (!transf) {
out$measure <- x$measure
attr(out$estimate, "measure") <- x$measure
}
if (.isTRUE(ddd$time)) {
time.end <- proc.time()
.print.time(unname(time.end - time.start)[3])
}
class(out) <- c("list.rma", "cumul.rma")
return(out)
}
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