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#' Return all path bootstraps as a long dataframe.
#' Columns of the dataframes are specified paths and rows are the estimated
#' coefficients for the paths at each bootstrap iteration.
#'
#' @param pls_boot bootstrapped PLS model
#'
#' @examples
#' data(mobi)
#'
#' mobi_mm <- constructs(
#' composite("Image", multi_items("IMAG", 1:5)),
#' composite("Expectation", multi_items("CUEX", 1:3)),
#' composite("Satisfaction", multi_items("CUSA", 1:3))
#' )
#'
#' mobi_sm <- relationships(
#' paths(from = c("Image", "Expectation"), to = "Satisfaction")
#' )
#'
#' pls_model <- estimate_pls(data = mobi,
#' measurement_model = mobi_mm,
#' structural_model = mobi_sm)
#'
#' pls_boot <- bootstrap_model(seminr_model = pls_model,
#' nboot = 50, cores = 2, seed = NULL)
#'
#' boot_paths_df(pls_boot)
#'
#' @export
boot_paths_df <- function(pls_boot) {
path_names <- apply(pls_boot$smMatrix, 1, \(path) {
paste(path['source'], '->', path['target'])
})
boot_paths <- apply(pls_boot$smMatrix, 1, \(path) {
pls_boot$boot_paths[path['source'], path['target'], 1:pls_boot$boots]
})
colnames(boot_paths) <- path_names
boot_paths
}
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