View source: R/splithalf_multiverse.R
splithalf.multiverse | R Documentation |
This function enables the user to run a multiverse of data processing options and extract the resulting (internal consistency) reliability estimates generated by splithalf. The user specifies a set of data processing decisions and passes this to the function, along with a splithalf object. The output can then be explored and plotted as desired.
splithalf.multiverse(input, specifications)
input |
splithalf object or list of splithalf objects |
specifications |
list of data processing specifications |
The (unofficial) function version name is "This function will let you get honey from a hornets nest"
Returns a multiverse object containing the reliability estimates and dataframes from all data processing specifications provided
## Not run: ## 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) ## can be plot with: multiverse.plot(multiverse = multiverse, title = "README multiverse") ## End(Not run)
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