## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment  = "#>",
  eval     = TRUE
)


## ----load---------------------------------------------------------------------
library(gtstats)

## ----minimal------------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl))

## ----overall------------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl), overall = TRUE)

## ----global-and-exceptions----------------------------------------------------
# Mean (SD) for every continuous variable
summary_table(
  birthwt,
  include = c(age, lwt, bwt, smoke),
  statistic = "mean_sd"
)

# Recommended summaries for all variables except maternal weight
summary_table(
  birthwt,
  include = c(age, lwt, bwt, smoke),
  statistic = c(lwt = "median_iqr")
)

## ----compact-binary-explicit--------------------------------------------------
summary_table(
  birthwt,
  by = low,
  include = c(smoke, ht, race),
  show_dichotomous = "single_row",
  value = c(smoke = "Yes", ht = "Yes")
) |>
  add_p()

## ----precision-and-labels-----------------------------------------------------
summary_table(
  birthwt,
  by = low,
  include = c(age, smoke),
  digits = c(continuous = 1, percent = 0, ci = 1),
  label = c(
    age = "Maternal age, years",
    smoke = "Smoking during pregnancy"
  )
)

## ----ci-layer-----------------------------------------------------------------
summary_table(
  mtcars,
  by = am,
  include = c(mpg, cyl, vs),
  layout = "separate"
) |>
  add_ci()

summary_table(
  mtcars,
  by = am,
  include = c(mpg, cyl, vs),
  layout = "separate"
) |>
  add_ci(vars = c(mpg, vs), conf.level = 0.90)

## ----separate-n-percent-layout------------------------------------------------
summary_table(
  mtcars,
  by = am,
  include = c(cyl, vs),
  categorical_layout = "separate"
)

## ----compact-binary-layout----------------------------------------------------
summary_table(
  birthwt,
  by = low,
  include = c(smoke, ht, race),
  show_dichotomous = "single_row",
  value = c(smoke = "Yes", ht = "Yes")
)

## ----mixed-continuous-formats-------------------------------------------------
summary_table(
  mtcars,
  by = am,
  include = c(mpg, wt, cyl),
  statistic = c(mpg = "mean_ci", wt = "median_iqr"),
  overall = "last"
)

## ----percentage-denominators--------------------------------------------------
summary_table(mtcars, by = am, overall = TRUE, include = c(cyl, vs), percent = "column")

summary_table(mtcars, by = am, overall = TRUE, include = c(cyl, vs), percent = "row")

summary_table(mtcars, by = am, overall = TRUE, include = c(cyl, vs), percent = "overall")

summary_table(mtcars, by = am, overall = TRUE, include = c(cyl, vs), categorical = "n")

## ----missing-rows-------------------------------------------------------------
summary_table(
  mtcars, by = am, overall = TRUE,
  include = c(mpg, wt, vs), missing = "ifany"
)

## ----missing-as-category------------------------------------------------------
missing_example <- data.frame(
  catheter = factor(
    c(rep("Yes", 32), rep(NA_character_, 68)),
    levels = c("No", "Yes")
  )
)

summary_table(
  missing_example,
  include = catheter,
  missing = "as_category"
)

## ----n-over-n-percent---------------------------------------------------------
summary_table(
  mtcars,
  by = am,
  include = cyl,
  categorical = "n_over_N_percent",
  percent = "column",
  digits = c(percent = 0)
)

## ----mean-ci------------------------------------------------------------------
summary_table(
  mtcars,
  include = c(mpg, wt),
  statistic = "mean_sd",
  layout = "separate"
) |>
  add_ci()

## ----separate-ci-layout-------------------------------------------------------
summary_table(
  birthwt,
  by = smoke,
  include = c(age, low),
  overall = "first",
  layout = "separate"
) |>
  add_ci()

## ----proportion---------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl), overall = TRUE) |>
  add_proportion(var = vs) |>
  to_gt()

## ----proportion-ci------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl), overall = TRUE) |>
  add_proportion(var = vs, level = "1", ci = TRUE) |>
  to_gt()

## ----total--------------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl), overall = TRUE) |>
  add_proportion(var = vs) |>
  add_total() |>
  to_gt()

## ----add-p-include------------------------------------------------------------
summary_table(birthwt, by = low, include = c(age, bwt, smoke)) |>
  add_p(include = -bwt)

## ----add-p--------------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl)) |>
  add_proportion(var = vs) |>
  add_p() |>
  to_gt()

## ----adjusted-p---------------------------------------------------------------
adjusted <- summary_table(mtcars, by = am, include = c(mpg, wt, cyl, vs)) |>
  add_p(p_adjust = "BH")

adjusted$p_values
adjusted$assumptions
adjusted$diagnostics
adjusted$denominators

## ----add-p-manual-------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl)) |>
  add_p(test = c(mpg = "welch_t", wt = "wilcox", cyl = "chisq")) |>
  to_gt()

## ----paired-------------------------------------------------------------------
dat <- data.frame(
  id     = rep(1:4, 2),
  period = c("before", "before", "before", "before",
             "after",  "after",  "after",  "after"),
  score  = c(10, 12, 9, 11, 13, 16, 11, 15)
)

summary_table(dat, by = period, include = score) |>
  add_p(paired = TRUE, id = id, test = "wilcox") |>
  to_gt()

## ----rate---------------------------------------------------------------------
summary_table(mtcars, by = am, overall = TRUE) |>
  add_rate(
    event      = carb,
    time       = cyl,
    label      = "Carburettor rate",
    multiplier = 1000
  ) |>
  to_gt()

## ----custom-------------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl), overall = TRUE) |>
  add_row(
    label   = "Study period",
    overall = "2020–2024",
    values  = c("am = 1" = "2020–2024", "am = 0" = "2020–2024")
  ) |>
  to_gt()

## ----full-workflow------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl), overall = TRUE) |>
  add_proportion(var = vs, level = "1", ci = TRUE) |>
  add_total() |>
  add_p() |>
  to_gt()

## ----style--------------------------------------------------------------------
summary_table(mtcars, by = am, include = c(mpg, wt, cyl), overall = TRUE) |>
  add_proportion(var = vs) |>
  add_total() |>
  add_p() |>
  customise_table(
    theme      = "journal",
    title      = "Table 1. Baseline characteristics by transmission type",
    col_labels = c(
      "Level"  = "",
      "am = 1" = "Manual",
      "am = 0" = "Automatic"
    ),
    row_labels = c(
      "mpg"    = "Miles per gallon",
      "wt"     = "Weight (1000 lbs)",
      "cyl"    = "Cylinders",
      "vs (1)" = "V-shaped engine"
    ),
    accent_color = "#123B7A"
  )

## ----journal-style-recipe-----------------------------------------------------
finished_table <- summary_table(
  birthwt,
  by = low,
  include = c(age, lwt, race, smoke),
  overall = "last",
  show_dichotomous = "single_row",
  value = c(smoke = "Yes")
) |>
  add_p() |>
  customise_table(
    theme = "journal",
    title = "Table 1. Maternal characteristics",
    spanning_header = "Birth-weight outcome",
    density = "compact",
    borders = "horizontal",
    font_size = 9,
    pvalue_style = "threshold",
    pvalue_digits = 3,
    accent_color = "#4A4A4A",
    show_footnotes = TRUE
  )

## ----display-only-relabel-----------------------------------------------------
summary_table(birthwt, by = low, include = c(race, smoke)) |>
  customise_table(
    col_labels = c(
      "low = Normal birth weight" = "Normal birth weight",
      "low = Low birth weight" = "Low birth weight"
    ),
    row_labels = c("Maternal race" = "Race"),
    level_labels = c("Yes" = "Smoker", "No" = "Non-smoker")
  )

## ----minimal-report-table-----------------------------------------------------
summary_table(birthwt, include = c(age, race, smoke)) |>
  customise_table(
    theme = "minimal",
    show_footnotes = FALSE,
    bold_labels = TRUE,
    density = "compact"
  )

## ----level-labels-------------------------------------------------------------
summary_table(mtcars, by = am, include = cyl, overall = TRUE) |>
  customise_table(
    level_labels = c(
      "4" = "4-cylinder",
      "6" = "6-cylinder",
      "8" = "8-cylinder"
    )
  )

## ----export-------------------------------------------------------------------
res <- summary_table(mtcars, by = am, include = c(mpg, wt, cyl), overall = TRUE) |>
  add_proportion(var = vs) |>
  add_total() |>
  add_p()

ft <- to_flextable(res)