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#' exclusion_criteria
#'
#'
#' @description Exclusion criteria
#' @param data a data object generated by the \code{multics::chop_css} function
#' @param cutoff cut off score
#' @return A tibble with a brace of smaller tibbles, with each sub-tibble including a data frame after each one of the exclusion criteria -- mentioned in the \code{multifear::chop_css} function -- is applied.
#' @details Here the different exclusion criteria are applied to the provided data.
#' @export
exclusion_criteria <- function(data, cutoff = 0) {
# Check data
chop_css_warning(data)
if (is.null(data$group)) {
group_new <-
data %>%
dplyr::mutate(group = rep("NULL", nrow(data))) %>%
dplyr::select(group)
} else{
group_new <- data %>%
dplyr::select(group) %>%
tibble::as_tibble()
}
# Exclude participants with no last 2 trials
data <-
data %>% dplyr::mutate(
diff_2_trials = cs1_l2trial - cs2_l2trial,
diff_4_trials = cs1_l2trial - cs2_l2trial,
diff_5_trials = cs1_l5trial - cs2_l5trial,
group = group
)
two_thre <- -99999999
four_thre <- -99999999
five_thre <- -99999999
data_details <- "full_data"
if (cutoff == 1){two_thre <- 0; data_details <- "last_2_trials"}
if (cutoff == 2){four_thre <- 0; data_details <- "last_4_trials"}
if (cutoff == 3){five_thre <- 0; data_details <- "last_5_trials"}
# Summarize full data
full_data <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
dplyr::select(dplyr::matches("cs1_t_|cs2_t_"), id, group)
ten_per <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
dplyr::select(cs1_t10per, cs1_b10per, cs2_t10per, cs2_b10per, id, group)
min_first <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
#dplyr::select(cs1_minfirst, cs2_minfirst, id, group)
dplyr::select(dplyr::contains("minfirst"), id, group)
th3_per <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
dplyr::select(dplyr::contains("33per"), id, group)
halves <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
dplyr::select(cs1_fhalf, cs1_lhalf, cs2_fhalf, cs2_lhalf, id, group)
fltrials <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
dplyr::select(cs1_ftrial, cs1_ltrial, cs2_ftrial, cs2_ltrial, id, group)
twenty_per <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
dplyr::select(dplyr::contains("20per"), id, group)
fl2trials <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
dplyr::select(cs1_f2trial, cs1_l2trial, cs2_f2trial, cs2_l2trial, id, group)
per2trials <- data %>%
dplyr::filter(diff_2_trials >= two_thre, diff_4_trials >= four_thre, diff_5_trials >= five_thre) %>%
dplyr::select(dplyr::matches("cs1_per2|cs2_per2"), id, group)
res <- tidyr::tibble(
used_data = list(
full_data = full_data,
ten_per = ten_per,
min_first = min_first,
th3_per = th3_per,
halves = halves,
fltrials = fltrials,
twenty_per = twenty_per,
fl2trials = fl2trials,
per2trials = per2trials#,
)
) %>%
dplyr::mutate(names = names(.$used_data), cutoff = data_details)
return(res)
}
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