sim-validation
Validaion Sim for splithalf
This script runs splithalf with many possible combinations of the options. Its main use is to ensure that the splithalf function
Splithalf()
# Thanks to Nathaniel Haines for the suggestion and the starting code (https://github.com/sdparsons/splithalf/issues/9).
set.seed(01042021)
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","congruent",
"incongruent","incongruent"),
length.out = n_participants * n_trials * n_blocks / 2),
RT = rnorm(n_participants * n_trials * n_blocks,
500,
200),
ACC = 1)
sim_data_acc <- 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","congruent",
"incongruent","incongruent"),
length.out = n_participants * n_trials * n_blocks / 2),
RT = rnorm(n_participants * n_trials * n_blocks,
500,
200),
ACC = c(rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .5),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .7),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .9),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .5),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .7),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .9)))params <- list(score = c("average",
"difference",
"difference_of_difference"),
halftype = c("oddeven",
"halfs",
"random"),
averae = c("mean",
"median") )
expand.grid(params) %>%
dplyr::arrange(., score, halftype)Response times
splithalf(data = sim_data,
outcome = "RT",
score = "average",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data,
outcome = "RT",
score = "average",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data,
outcome = "RT",
score = "average",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data,
outcome = "RT",
score = "average",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data,
outcome = "RT",
score = "average",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean",
plot = TRUE)
splithalf(data = sim_data,
outcome = "RT",
score = "average",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median",
plot = TRUE)
splithalf(data = sim_data,
outcome = "RT",
score = "difference",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data,
outcome = "RT",
score = "difference",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data,
outcome = "RT",
score = "difference",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data,
outcome = "RT",
score = "difference",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data,
outcome = "RT",
score = "difference",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean",
plot = TRUE)
splithalf(data = sim_data,
outcome = "RT",
score = "difference",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median",
plot = TRUE)
splithalf(data = sim_data,
outcome = "RT",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data,
outcome = "RT",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data,
outcome = "RT",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data,
outcome = "RT",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data,
outcome = "RT",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean",
plot = TRUE)
splithalf(data = sim_data,
outcome = "RT",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent",
average = "median",
plot = TRUE)
Average accuracy rates
splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "average",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "average",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "average",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "average",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "average",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean",
plot = TRUE)
splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "average",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median",
plot = TRUE)
splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean",
plot = TRUE)
splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median",
plot = TRUE)
splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "oddeven",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "halfs",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median")splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean",
plot = TRUE)
splithalf(data = sim_data_acc,
outcome = "accuracy",
score = "difference_of_difference",
conditionlist = c("A", "B"),
halftype = "random",
permutations = 500,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "median",
plot = TRUE)
multiverse
Runs several multiverse
set.seed(01042021)
n_participants <- 80 ## sample size
n_trials <- 120
n_blocks <- 2
sim_data_mv <- 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(1,2),
each = n_trials,
length.out = n_participants * n_trials * n_blocks),
trial_type = rep(c("congruent","congruent",
"incongruent","incongruent"),
length.out = n_participants * n_trials * n_blocks / 2),
RT = rnorm(n_participants * n_trials * n_blocks,
500,
200),
ACC = c(rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .5),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .7),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .9),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .5),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .7),
rbinom(n_participants *
n_trials *
n_blocks / 6,
1, .9)))specifications <- list(
ACC_cutoff = c(0, 0.5),
RT_min = c(0, 200),
RT_max = c(2000, 3000),
RT_sd_cutoff = c(0, 2),
split_by = c("subject", "trial"),
averaging_method = c("mean")
)internal consistency
mv_splithalf <- splithalf(data = sim_data,
outcome = "RT",
score = "difference",
conditionlist = c("A"),
halftype = "random",
permutations = 50,
var.RT = "RT",
var.condition = "block_name",
var.participant = "participant_number",
var.compare = "trial_type",
var.ACC = "ACC",
compare1 = "congruent",
compare2 = "incongruent",
average = "mean")
multiverse <- splithalf.multiverse(input = mv_splithalf,
specifications = specifications)
test-retest
icc2 <- testretest.multiverse(data = sim_data_acc,
specifications,
test = "ICC2",
score = "difference",
var.participant = "participant_number",
var.ACC = "ACC",
var.RT = "RT",
var.time = "block_name",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent")
multiverse.plot(icc2)
icc3 <- testretest.multiverse(data = sim_data_acc,
specifications,
test = "ICC3",
score = "difference",
var.participant = "participant_number",
var.ACC = "ACC",
var.RT = "RT",
var.time = "block_name",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent")
multiverse.plot(icc3)
retest_cor <- testretest.multiverse(data = sim_data_acc,
specifications,
test = "cor",
score = "difference",
var.participant = "participant_number",
var.ACC = "ACC",
var.RT = "RT",
var.time = "block_name",
var.compare = "trial_type",
compare1 = "congruent",
compare2 = "incongruent")
multiverse.plot(retest_cor)