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#' Check proportion of reliability estimates from the multiverse analyses above or below a set threshold
#'
#' This function examines the output from splithalf_multiverse or testretest_multiverse to extract the proportions of estimates above or below a set threshold (can be the estimate or the upper or lower CI estimates).
#' The (unofficial) function version name is "This function will get you up to here with it"
#'
#' @param multiverse multiverse object
#' @param threshold threshold to look for, e.g. 0.7
#' @param use set to check the reliability "estimates", or the "upper" or "lower" CIs
#' @param dir look "above" or "below" the 'use' at the set threshold
#' @examples
#' \dontrun{
#' ## see online documentation for examples
#' https://github.com/sdparsons/splithalf
#' ## also see https://psyarxiv.com/y6tcz
#'
#' ## example simulated data
#' n_participants = 60 ## sample size
#' n_trials = 80
#' n_blocks = 2
#' sim_data <- data.frame(participant_number = rep(1:n_participants,
#' each = n_blocks * n_trials),
#' trial_number = rep(1:n_trials,
#' times = n_blocks * n_participants),
#' block_name = rep(c("A","B"),
#' each = n_trials,
#' length.out = n_participants * n_trials * n_blocks),
#' trial_type = rep(c("congruent","incongruent"),
#' length.out = n_participants * n_trials * n_blocks),
#' RT = rnorm(n_participants * n_trials * n_blocks,
#' 500,
#' 200),
#' ACC = 1)
#'
#' ## specify several data processing decisions
#' specifications <- list(RT_min = c(0, 100, 200),
#' RT_max = c(1000, 2000),
#' averaging_method = c("mean", "median"))
#' ## run splithalf, and save the output
#' difference <- splithalf(data = sim_data,
#' outcome = "RT",
#' score = "difference",
#' conditionlist = c("A"),
#' halftype = "random",
#' permutations = 5000,
#' var.RT = "RT",
#' var.condition = "block_name",
#' var.participant = "participant_number",
#' var.compare = "trial_type",
#' var.ACC = "ACC",
#' compare1 = "congruent",
#' compare2 = "incongruent",
#' average = "mean")
#'
#' ## run splithalf.multiverse to perform the multiverse of data processing
#' ## and reliability estimation
#' multiverse <- splithalf.multiverse(input = difference,
#' specifications = specifications)
#'
#'
#' ## the threshold function can be used to return the number of estimates
#' ## above or below a certain threshold
#'
#' threshold(multiverse = multiverse,
#' threshold = 0.7,
#' use = "estimate",
#' dir = "above")
#' }
#' @useDynLib splithalf, .registration = TRUE
#' @rdname multiverse.plot
#' @export
threshold <- function(multiverse,
threshold,
use = "estimate",
dir = "above") {
tmp <- 1:multiverse$nS
if(use == "estimate") {
tmp <- multiverse$estimates$estimate
}
if(use == "lower") {
tmp <- multiverse$estimates$low
}
if(use == "upper") {
tmp <- multiverse$estimates$high
}
if(dir == "above") {
threshold <- sum(tmp > threshold) / length(tmp)
}
if(dir == "below") {
threshold <- sum(tmp < threshold) / length(tmp)
}
return(threshold)
}
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