leave1out.rma.uni <- function(x, digits, transf, targs, progbar=FALSE, ...) {
mstyle <- .get.mstyle()
.chkclass(class(x), must="rma.uni", notav=c("robust.rma", "rma.ls", "rma.gen", "rma.uni.selmodel"))
na.act <- getOption("na.action")
if (!is.element(na.act, c("na.omit", "na.exclude", "na.fail", "na.pass")))
stop(mstyle$stop("Unknown 'na.action' specified under options()."))
if (!x$int.only)
stop(mstyle$stop("Method only applicable to models without moderators."))
if (x$k == 1L)
stop(mstyle$stop("Stopped because k = 1."))
if (is.null(x$yi.f) || is.null(x$vi.f))
stop(mstyle$stop("Information needed to carry out a leave-one-out analysis is not available in the model object."))
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"))
if (.isTRUE(ddd$time))
time.start <- proc.time()
#########################################################################
beta <- rep(NA_real_, x$k.f)
se <- rep(NA_real_, x$k.f)
zval <- rep(NA_real_, x$k.f)
pval <- rep(NA_real_, x$k.f)
ci.lb <- rep(NA_real_, x$k.f)
ci.ub <- rep(NA_real_, x$k.f)
QE <- rep(NA_real_, x$k.f)
QEp <- rep(NA_real_, x$k.f)
tau2 <- rep(NA_real_, x$k.f)
I2 <- rep(NA_real_, x$k.f)
H2 <- rep(NA_real_, x$k.f)
### elements that need to be returned
outlist <- "beta=beta, se=se, zval=zval, pval=pval, ci.lb=ci.lb, ci.ub=ci.ub, QE=QE, QEp=QEp, tau2=tau2, I2=I2, H2=H2"
### note: skipping NA cases
### also: it is possible that model fitting fails, so that generates more NAs (these NAs will always be shown in output)
if (progbar)
pbar <- pbapply::startpb(min=0, max=x$k.f)
for (i in seq_len(x$k.f)) {
if (progbar)
pbapply::setpb(pbar, i)
if (!x$not.na[i])
next
args <- list(yi=x$yi.f, vi=x$vi.f, weights=x$weights.f, intercept=TRUE, method=x$method, weighted=x$weighted,
test=x$test, level=x$level, tau2=ifelse(x$tau2.fix, x$tau2, NA), control=x$control, subset=-i, skipr2=TRUE, outlist=outlist)
res <- try(suppressWarnings(.do.call(rma.uni, args)), silent=TRUE)
if (inherits(res, "try-error"))
next
beta[i] <- res$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$QEp
tau2[i] <- res$tau2
I2[i] <- res$I2
H2[i] <- res$H2
}
if (progbar)
pbapply::closepb(pbar)
#########################################################################
### if requested, apply transformation function
if (is.function(transf)) {
if (is.null(targs)) {
beta <- sapply(beta, transf)
se <- rep(NA_real_, x$k.f)
ci.lb <- sapply(ci.lb, transf)
ci.ub <- sapply(ci.ub, transf)
} else {
beta <- sapply(beta, transf, targs)
se <- rep(NA_real_, x$k.f)
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]
#########################################################################
if (na.act == "na.omit") {
out <- list(estimate=beta[x$not.na], se=se[x$not.na], zval=zval[x$not.na], pval=pval[x$not.na], ci.lb=ci.lb[x$not.na], ci.ub=ci.ub[x$not.na], Q=QE[x$not.na], Qp=QEp[x$not.na], tau2=tau2[x$not.na], I2=I2[x$not.na], H2=H2[x$not.na])
out$slab <- x$slab[x$not.na]
}
if (na.act == "na.exclude" || na.act == "na.pass") {
out <- list(estimate=beta, se=se, zval=zval, pval=pval, ci.lb=ci.lb, ci.ub=ci.ub, Q=QE, Qp=QEp, tau2=tau2, I2=I2, H2=H2)
out$slab <- x$slab
}
if (na.act == "na.fail" && any(!x$not.na))
stop(mstyle$stop("Missing values in results."))
if (is.element(x$test, c("knha","adhoc","t")))
names(out)[3] <- "tval"
### remove tau2 for FE/EE/CE models
if (is.element(x$method, c("FE","EE","CE")))
out <- out[-9]
out$digits <- digits
out$transf <- transf
if (.isTRUE(ddd$time)) {
time.end <- proc.time()
.print.time(unname(time.end - time.start)[3])
}
class(out) <- "list.rma"
return(out)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.