#' tibbleOne: tidy characteristics tables
#'
#' @description In many academic papers, table 1 shows participant
#' characteristics, often stratified by a categorical variable
#' such as treatment group. There are many excellent packages
#' available to compute the numbers in table 1. This package
#' focuses on getting those numbers into a nice format that
#' works with R Markdown. Additionally, there is a fair amount
#' of diversity in researchers' preferred writing mediums.
#' Some may prefer LaTeX, while others want to work in Microsoft
#' Word. Recently, html documents have grown more common
#' for research papers. tibbleOne is meant to be applicable for
#' each of these settings, and should meet the needs of most
#' studies.
#'
#' To learn more about tibbleOne, start with the vignettes:
#' `browseVignettes(package = "tibbleOne")`
#'
#' @importFrom knitr kable
#'
#' @importFrom officer fp_border
#'
#' @importFrom flextable flextable as_flextable as_grouped_data compose
#' as_paragraph set_header_labels fontsize align padding theme_box
#' as_chunk
#'
#' @importFrom tibble tibble as_tibble enframe deframe
#'
#' @importFrom forcats fct_inorder fct_relevel fct_explicit_na
#'
#' @importFrom labelled var_label set_variable_labels var_label<-
#'
#' @importFrom tidyr spread unnest nest gather
#'
#' @importFrom tidyselect vars_select vars_pull
#'
#' @importFrom kableExtra footnote_marker_number footnote_marker_symbol
#' footnote_marker_alphabet group_rows add_indent add_header_above
#' add_footnote
#'
#' @importFrom stringr str_detect fixed str_split
#'
#' @importFrom rlang %||% is_character ensyms enquo
#'
#' @importFrom vctrs vec_size vec_is_empty
#'
#' @importFrom purrr map pmap map_dfr map_chr map_dbl map_lgl map_int
#' set_names modify pluck reduce flatten map2_lgl map2_chr
#'
#' @importFrom stats glm lm sd qnorm coef vcov as.formula update.formula
#' na.omit terms lm t.test wilcox.test kruskal.test anova quantile
#' chisq.test
#'
#' @importFrom glue glue glue_collapse
#'
#' @importFrom magrittr %>% %<>% set_colnames add use_series
#'
#' @importFrom dplyr select mutate filter group_by top_n pull mutate_if
#' left_join bind_rows case_when slice select_at everything arrange
#' rename if_else
#'
"_PACKAGE"
## quiets concerns of R CMD check re: the .'s that appear in pipelines
if(getRversion() >= "2.15.1")
utils::globalVariables(
c(
".",
".x",
'id',
"key",
"abbr",
"unit",
"note",
"name",
"type",
"label",
"group",
"value",
".data",
".strat",
"tbl_one",
"tbl_val",
"n_unique",
"variable",
'fun_descr',
'test_descr',
'group.row.id',
'bad_table_specs',
'specs_table_vals'
)
)
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