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#' @method summary MetaForest
#' @export
summary.MetaForest <- function(object, ...) {
if(inherits(object, "cluster_mf")){
mf_type <- "Clustered MetaForest"
k <- paste0("Forest 1: ", sum(is.na(object$forest$cluster_forests$rf1$predictions)), ", Forest 2: ", sum(is.na(object$forest$cluster_forests$rf2$predictions)))
num.trees <- paste0("Two forests of length ", object$forest$num.trees/2)
} else {
mf_type <- "MetaForest"
k <- object$forest$num.samples
num.trees <- object$forest$num.trees
}
forest.table <-
c(
type = mf_type,
k = k,
M = object$forest$num.independent.variables,
num.trees = num.trees,
mtry = object$forest$mtry,
min.node.size = object$forest$min.node.size,
MSEoob = object$forest$prediction.error,
R2oob = object$forest$r.squared
)
rma.table <- cbind(
tau2 = c(object$rma_before$tau2, object$rma_after$tau2),
tau2_SE = c(object$rma_before$se.tau2, object$rma_after$se.tau2),
`I^2` = c(object$rma_before$I2, object$rma_after$I2),
`H^2` = c(object$rma_before$H2, object$rma_after$H2),
"Q-test" = c(object$rma_before$QE, object$rma_after$QE),
df = c(object$rma_before$k - object$rma_before$p, object$rma_after$k - object$rma_after$p),
Q_p = c(object$rma_before$QEp, object$rma_after$QEp),
Intercept = c(object$rma_before$beta, object$rma_after$beta),
se = c(object$rma_before$se, object$rma_after$se),
ci.lb = c(object$rma_before$ci.lb, object$rma_after$ci.lb),
ci.ub = c(object$rma_before$ci.ub, object$rma_after$ci.ub),
p = c(object$rma_before$pval, object$rma_after$pval)
)
sum <- list(forest = forest.table, rma = rma.table)
class(sum) <- "summary.MetaForest"
sum
}
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