Real Examples of Clinical Outputs using ksTFL

raw <- tibble(
  SECTION = c(
    rep("Age (years)", 6),
    rep("Sex", 3),
    rep("Race", 4)
  ),
  STAT = c(
    "n", "Mean (SD)", "Median", "Q1; Q3", "Min; Max", "p-value (ANOVA)",
    "Female", "Male", "p-value (Fisher)",
    "White", "Asian", "Black", "p-value (Fisher)"
  ),
  DRUGX = c("160", "55.2 (12.4)", "54.0", "47.0; 64.0", "18; 82", "",
            "88 (55.0%)", "72 (45.0%)", "",
            "130 (81.2%)", "18 (11.2%)", "12 (7.5%)", ""),
  PLCB  = c("158", "56.0 (11.9)", "55.0", "48.0; 63.0", "20; 81", "",
            "90 (57.0%)", "68 (43.0%)", "",
            "124 (78.5%)", "22 (13.9%)", "12 (7.6%)", ""),
  TOTAL = c("318", "55.6 (12.1)", "54.0", "47.5; 63.5", "18; 82", "",
            "178 (56.0%)", "140 (44.0%)", "",
            "254 (79.9%)", "40 (12.6%)", "24 (7.5%)", ""),
  MODELVAL = c(NA, NA, NA, NA, NA, "0.041",
               NA, NA, ">0.999",
               NA, NA, NA, "0.772")
) %>%
  group_by(SECTION) %>%
  mutate(SECTION_ID = cur_group_id()) %>%
  ungroup()

spec <- create_table(raw) %>%

  # --- Titles and footnotes ---
  # Multi-line title: table number on first line, description on second.
  # toclevel = 1 makes this entry appear in the Table of Contents.
  add_title(
    c("Table S1",
      "Demographic and Baseline Characteristics"),
    toclevel = 1
  ) %>%
  # Secondary title in italics for the analysis population label
  add_title("Full Analysis Set", styleRef = "font_italic") %>%
  add_footnote(c(
    "Values are shown as n (%), mean (SD), median, or quartiles.",
    "P-values shown for section-level inferential tests."
  )) %>%

  # --- Column definitions ---
  # Hide helper columns: they won't appear in the document, but remain
  # available for compute_cols() conditions. This is the "invisible column"
  # pattern — SECTION drives group headers, SECTION_ID drives spacing and
  # page breaks, MODELVAL carries p-values for conditional formatting.
  define_cols(c(SECTION, SECTION_ID, MODELVAL), isVisible = FALSE) %>%

  # The statistics column: left-aligned header, values indented one level
  # to sit beneath the bold section headers inserted by c_addrow() below.
  define_cols(STAT,
    label     = "Parameter<br>  Statistic",
    labelStyleRef = "text_left",
    valueStyleRef = "indent_1"
  ) %>%

  # Treatment-arm columns: centred values, equal width, with N in the header.
  define_cols(c(DRUGX, PLCB, TOTAL),
    label     = c("DrugX<br>(N=160)", "Placebo<br>(N=158)", "Total<br>(N=318)"),
    valueStyleRef = "text_center",
    colWidth  = "16%"
  ) %>%

  # --- Conditional row actions (compute_cols) ---

  # 1. Section headers: for the first row of each SECTION
  #    group, insert a bold header row above it, pulling the
  #    text from the hidden SECTION column.
  compute_cols(
    firstOf(SECTION),
    c_addrow("above", value_from = SECTION, styleRef = "font_bold")
  ) %>%

  # 2. P-value rows: when MODELVAL is not NA, merge the DrugX and Placebo
  #    cells into one (with a thin top border and centred italic text),
  #    italicise the STAT label, and append the p-value after the merged cell.
  compute_cols(
    !is.na(MODELVAL),
    c_merge(c(DRUGX, PLCB), styleRef = f_combine("text_center", "bt_th", "i")),
    c_style(STAT, "i"),
    c_glue(DRUGX, "after", glue_col = MODELVAL)
  ) %>%

  # 3. Spacers: insert a thin empty row below each section for visual separation
  compute_cols(
    lastOf(SECTION_ID),
    c_addrow("below", styleRef = "row_h4")
  ) %>%

  # 4. Page break: force a new page before the Race section (group 3)
  compute_cols(
    SECTION_ID == 3 & firstOf(SECTION_ID),
    c_pageBreak()
  ) %>%

  # Document-level settings: narrow content area, no extra spacing
  set_document(
    contentWidth = "75%",
    topEmptyLine = "0pt",
    bottomEmptyLine = "0pt"
  )

create_report(spec) %>% write_doc("example_01")

spec <- set_document(spec, docTemplate = 'Navy_Pro')
create_report(spec) %>% write_doc("example_01_navy")

### Build the specification object

drg_N   <- 16
plcb_N  <- 17
total_N <- 33

spec_dm_01 <- create_table(data) %>% 
  add_title(
    c("Таблица 1.2",
      "Демографические и другие исходные характеристики"),
    toclevel = 1
  ) %>% 
  add_title("Популяция FAS", styleRef = 'font_italic') %>% 
  add_footnote('Источник: Перечень 16.3; Перечень 16.33') %>% 
  # The CAT1 variable holds the category name. We want those
  # names to appear in the CAT2 column as section headers,
  # so we hide CAT1. We also hide the helper columns SECTORD1
  # and modelval (whose values we place into other cells):
  
  define_cols(c(CAT1, SECTORD1, modelval), isVisible = F) %>% 
  # First value of each CAT1 group becomes an extra header row:
  compute_cols(
    # built-in helper: first value within a group
    # (can also define composite groups from several variables)
    firstOf(CAT1),
    # Insert a bold row above with the value from CAT1
    c_addrow('above',
             value_from = CAT1,
             styleRef = 'font_bold')
  ) %>% 
  ## Indent CAT2 values to the right relative to the header.
  ## This can be done in two ways...
  # Method 1: via a per-row rule:
  #   compute_cols(!is.na(CAT2), c_style(CAT2, 'indent_1'))
  # Method 2: by setting the column style directly.
  #   Method 2 is preferable here because we apply the same
  #   style to every value in the column; doing it per-row via
  #   compute_cols creates unnecessary rendering overhead.
  # We also define the column label and header style:
  define_cols(CAT2,
              label = 'Параметр<br>  Статистика',
              valueStyleRef = 'indent_1',
              labelStyleRef = 'text_left') %>% 
  # Labels for the remaining treatment-arm columns:
  define_cols(c(RPH104, PLCB, TOTAL),
              label = c(
                paste0('Drug-001', '<br>(N=', drg_N, ')'),
                paste0('Плацебо', '<br>(N=', plcb_N, ')'),
                paste0('Всего', '<br>(N=', total_N, ')')
              ),
              # indent numbers from cell borders
              valueStyleRef = 'indent_1',
              colWidth = '15%'
  ) %>% 
  define_cols(everything(), valueStyleRef = 'fs_8') %>% 
  # Display modelval in a merged cell spanning RPH104 + PLCB:
  compute_cols(
    !is.na(modelval),
    # Merge cells; centre the value and draw a thin top border
    # to show it relates to both treatment columns:
    c_merge(c(RPH104, PLCB),
            styleRef = f_combine('text_center', 'bt_th', 'i')),
    c_style(CAT2, 'i'),
    # Append modelval into the merged cell
    c_glue(RPH104, 'after', glue_col = modelval)
  ) %>% 
  # Separators between groups
  compute_cols(
    lastOf(SECTORD1),
    c_addrow('below', styleRef = 'row_h4')
  ) %>% 
  # Manual page break: first 3 categories on page one,
  # the rest on page two:
  compute_cols(
    SECTORD1 == 4 & firstOf(SECTORD1),
    c_pageBreak()
  ) %>% 
  set_document(
    contentWidth = '75%',
    # Place footnotes in the document footer section
    footnotePlace = 'doc_footer',
    # Use an alternative embedded template
    docTemplate = 'Classic_landscape_times'
  ) 

  create_report(spec_dm_01) %>% write_doc("example_02_demog")

# --- Build the table specification ---
spec <- create_table(tbl) %>%

  # --- Custom styles ---
  # Define a smaller font size for the dense numeric columns,
  # and extra spacing after the title block for readability.
  add_style("font_small", s_font(font_size = "8pt")) %>%
  add_style("spacing_after10",
    s_paragraph(spacing = s_spacing(after = "10pt"))
  ) %>%

  # --- Title block ---
  # Three-line title: table number, full description, and population label.
  # toclevel = 1 adds it to the Table of Contents.
  add_title(c(
    "Table 11.32",
    "Frequency of AEs by System Organ Class, and Severity.",
    "SS Sub-population, Primary Enrolment into OLE"
  ), toclevel = 1, styleRef = "spacing_after10") %>%

  # --- Page layout ---
  # Dynamic page numbering in the footer
  add_footer("", "Page {PAGE} of {NUMPAGES}", "") %>%
  # Landscape A4 with tight margins — necessary to fit 16 columns
  set_page_style(
    page = p_page(
      size = "A4",
      orientation = "landscape",
      margins = p_margins(
        top = "12mm",
        bottom = "12mm",
        left = "5mm",
        right = "5mm",
        header = "8mm",
        footer = "8mm"
      )
    )
  ) %>%

  # --- Column definitions ---
  # Hide SOC_GROUP — it is used only by compute_cols() to insert
  # bold SOC header rows and trigger page breaks between groups.
  define_cols(SOC_GROUP, isVisible = FALSE) %>%

  # SOC / Preferred Term: left-aligned, repeats on page breaks (isID = TRUE)
  # so readers always know which SOC they are looking at.
  define_cols(SOC_PT,
              label = "MedDRA SOC",
              isID = TRUE,
              labelStyleRef = "text_left",
              valueStyleRef = f_combine("text_left", "font_small"),
              colWidth = "18%"
  ) %>%
  # Severity column: also repeats on continuation pages.
  define_cols(SEVERITY,
              label = "Severity",
              isID = TRUE,
              labelStyleRef = "text_left",
              valueStyleRef = f_combine("text_left", "font_small"),
              colWidth = "13%"
  ) %>%
  # All 14 numeric columns share the same layout: centred, small font,
  # equal width. The label vector alternates "n (%)" and "E" (events).
  define_cols(
    c(
      TRT_N, TRT_E,
      FU_0_6_N, FU_0_6_E,
      FU_GT6_N, FU_GT6_E,
      FU_0_8_N, FU_0_8_E,
      FU_GT8_N, FU_GT8_E,
      FU_TOTAL_N, FU_TOTAL_E,
      GRAND_N, GRAND_E
    ),
    label = rep(c("n (%)", "E"), 7),
    #labelStyleRef = f_combine("text_center","to_90"),
    labelStyleRef = "text_center",
    valueStyleRef = f_combine("text_center", "font_small"),
    colWidth = "4.3%"
  ) %>%

  # --- Multi-level spanning headers (3 tiers) ---
  # Spanning headers group columns visually. stubOrder controls the
  # vertical stacking order (1 = closest to column labels, 3 = top).

  # Tier 1 (stubOrder = 1): individual period sub-headers
  add_span_header(
    cols = c(TRT_N, TRT_E),
    label = "Treatment Period<br>n (%)",
    stubOrder = 1
  ) %>%
  add_span_header(
    cols = c(GRAND_N, GRAND_E),
    label = "Overall<br>n (%)",
    stubOrder = 1
  ) %>%
  add_span_header(
    cols = c(FU_0_6_N, FU_0_6_E),
    label = "0-6 wks after<br>last dose",
    stubOrder = 1
  ) %>%
  add_span_header(
    cols = c(FU_GT6_N, FU_GT6_E),
    label = ">6 wks after<br>last dose",
    stubOrder = 1
  ) %>%
  add_span_header(
    cols = c(FU_0_8_N, FU_0_8_E),
    label = "0-8 wks after<br>last dose",
    stubOrder = 1
  ) %>%
  add_span_header(
    cols = c(FU_GT8_N, FU_GT8_E),
    label = ">8 wks after<br>last dose",
    stubOrder = 1
  ) %>%
  add_span_header(
    cols = c(FU_TOTAL_N, FU_TOTAL_E),
    label = "Total",
    stubOrder = 1
  ) %>%
  # Tier 2 (stubOrder = 2): groups all follow-up sub-periods under one
  # banner, making it clear that the five sub-columns all belong to
  # the Safety Follow-up Period.
  add_span_header(
    cols = c(FU_0_6_N, FU_0_6_E, FU_GT6_N, FU_GT6_E, 
             FU_0_8_N, FU_0_8_E, FU_GT8_N, FU_GT8_E, FU_TOTAL_N, FU_TOTAL_E),
    label = "Safety Follow-up Period<br>n (%)",
    stubOrder = 2
  ) %>%
  # Tier 3 (stubOrder = 3): top-level drug arm header spanning all
  # numeric columns. The label is a two-element vector (drug name + N).
  add_span_header(
    cols = c(
      TRT_N, TRT_E,
      FU_0_6_N, FU_0_6_E, FU_GT6_N, FU_GT6_E,
      FU_0_8_N, FU_0_8_E, FU_GT8_N, FU_GT8_E,
      FU_TOTAL_N, FU_TOTAL_E,
      GRAND_N, GRAND_E
    ),
    label = c("DrugX", sprintf("N=%d", N)),
    stubOrder = 3) %>%

  # --- Conditional row actions ---
  # Insert a bold SOC header row above the first row of each SOC group.
  # The "Any AE" group already has its own label in the data, so we skip it.
  compute_cols(
    firstOf(SOC_GROUP) & SOC_GROUP != "Any AE",
    c_addrow("above", value_from = SOC_GROUP, styleRef = "font_bold")
  ) %>%
  # Force a page break before SOC1 so the "Any AE" summary stands alone
  # on the first page and per-SOC detail starts on a fresh page.
  compute_cols(
    SOC_GROUP == "SOC1" & firstOf(SOC_GROUP),
    c_pageBreak()
  ) %>%
  # Bold the SOC-level totals: rows where SEVERITY is blank represent
  # the overall count for that SOC (not broken down by severity grade).
  compute_cols(
    SEVERITY == "",
    c_style(c(SOC_PT, SEVERITY), styleRef = "font_bold")
  ) %>%
  # Use a regulatory-style template (Arial font, conservative borders)
  set_document(docTemplate = 'Regulatory_Arial')

## Write the document
create_report(spec) %>% write_doc("example_03_ae")

spec_lbl_01 <- create_table(lab_listing) %>%
    
    # --- Title and dynamic subtitle ---
    # toclevel = 1 creates the top-level TOC entry for this listing.
    add_title(c("Listing 16.1", "Laboratory Data"), toclevel = 1) %>%
    # Dynamic subtitle: #ByGroup1/2/3 are replaced at render time with the
    # current values of the grouping columns (ID, AGE, SEX).
    # toclevel = 2 creates a nested TOC entry per subject.
    add_subtitle(
        "Subject: #ByGroup1, Sex: #ByGroup3, Age (years): #ByGroup2",
        toclevel = 2
    ) %>%
    add_footnote('H, L - Value Outside Normal Ranges') %>%
    
    # --- Column definitions ---
    # Hide subject-level columns and mark them as grouping variables.
    # isGrouping = TRUE triggers automatic page breaks when any of these
    # columns change value, and populates the #ByGroupN placeholders.
    define_cols(
        c(ID, SEX, AGE),
        isVisible = FALSE, 
        isGrouping = TRUE
    ) %>%
    
    # Lab parameter columns: rotated 90° headers (to_90), left-aligned,
    # top-aligned (va_t).
    define_cols(
        c(-TRT, -VISIT, -DATE),
        labelStyleRef = f_combine(
            'al', 'va_t', 'to_90'
        )
    ) %>%
    
    # Identifier columns: Treatment, Visit 
    define_cols(c(TRT, VISIT, DATE),
                            label = c('Treatment', 'Visit', 'Date'),
                            valueStyleRef = 'i' # Italicise Treatment and Visit values for visual distinction
    ) %>% 
    #Hide Normal Ranges columns - we will use them to mark the lab value itself
    define_cols( ends_with('NR'),   isVisible = FALSE   ) %>% 
    # Lab parameter columns (positions 7-15): narrow equal
    # widths, descriptive labels
    define_cols(c(ALT, AST, BILI, HGB, PH, WBCU),
                            colWidth = '7%', #set equal width for all result columns
                            label = c('ALT (U/L)', 'AST (U/L)',
                                'Bilirubin (g/dL)', 'Hemoglobin (g/dL)', 
                                'pH',   'Leukocytes, urine (/HPF)'
                            ),
                            missings = 'NC' #defines how to report NA values
    ) %>%
    
    # --- Conditional formatting ---
    # Flag abnormal ALT values: if ALTNR is Low append 'L' to the value, 
    #                           if is High append 'H' to the value
    compute_cols(
            (ALTNR == 'low') %>% replace_na(FALSE),
            c_style(ALT, styleRef = 'fc_green'),
            c_glue(ALT, 'after', text = '<sup>L</sup>')
    ) %>%
    compute_cols(
            (ALTNR == 'high') %>% replace_na(FALSE),
            c_style(ALT, styleRef = 'fc_red'),
            c_glue(ALT, 'after', text = '<sup>H</sup>')
        ) %>%
    # Repeat the same trick with other result 
    compute_cols(
        (ASTNR == 'low') %>% replace_na(FALSE),
        c_style(AST, styleRef = 'fc_green'),
        c_glue(AST, 'after', text = '<sup>L</sup>')
    ) %>%
    compute_cols(
        (ASTNR == 'high') %>% replace_na(FALSE),
        c_style(AST, styleRef = 'fc_red'),
        c_glue(AST, 'after', text = '<sup>H</sup>')
    ) %>%
    compute_cols(
        (HGBNR == 'low') %>% replace_na(FALSE),
        c_style(HGB, styleRef = 'fc_green'),
        c_glue(HGB, 'after', text = '<sup>L</sup>')
    ) %>%
    compute_cols(
        (HGBNR == 'high') %>% replace_na(FALSE),
        c_style(HGB, styleRef = 'fc_red'),
        c_glue(HGB, 'after', text = '<sup>H</sup>')
    ) %>%
    compute_cols(
        (BILINR == 'low') %>% replace_na(FALSE),
        c_style(BILI, styleRef = 'fc_green'),
        c_glue(BILI, 'after', text = '<sup>L</sup>')
    ) %>%
    compute_cols(
        (BILINR == 'high') %>% replace_na(FALSE),
        c_style(BILI, styleRef = 'fc_red'),
        c_glue(BILI, 'after', text = '<sup>H</sup>')
    ) %>% 
    # --- Document settings ---
    set_document(
        docTemplate = 'Default',
        topEmptyLine = '6pt',
        bottomEmptyLine = '6pt',
  
    )

## Write the document with a Table of Contents page
create_report(spec_lbl_01) %>% write_doc("example_04_list", toc = TRUE)

spec_lbl_02 <- spec_lbl_01 %>%
  # Add a column break at PH — all columns from PH onward move to a new page.
  # The Treatment, Visit, and Date columns (isID = TRUE) repeat automatically.
  define_cols(PH, isColBreak = TRUE)

create_report(spec_lbl_02) %>% write_doc("example_04_list_colbr", toc = TRUE)

library(ggplot2)

# --- Figure 1: Fuel efficiency scatter plot from mtcars ---
# A straightforward scatter plot coloured by cylinder count.
t.fig <- ggplot(mtcars, aes(x = wt, y = mpg, colour = factor(cyl))) +
  geom_point(size = 3, alpha = 0.8) +
  scale_colour_manual(
    name   = "Cylinders",
    values = c("4" = "#2166AC", "6" = "#F4A582", "8" = "#D6604D")
  ) +
  labs(
    x = "Weight (1000 lbs)",
    y = "Miles per Gallon"
  ) +
  theme_bw(base_size = 11) +
  theme(legend.position = "bottom")

# Wrap the ggplot in a figure spec, then add titles and footnotes.
# toclevel = 1 adds this figure to the TOC.
t.fig.spec <- t.fig %>% create_figure() %>%
  add_title(
    c("Study Motor Trend",
      "Figure 1: Fuel Efficiency by Vehicle Weight"),
    toclevel = 1
  ) %>%
  add_subtitle("All vehicles, 1974") |>
  add_footnote("Source: 1974 Motor Trend US magazine (n = 32 vehicles).")

# figureScaleMode = "fitPage" scales the image to fill the available area.
t.fig.spec <- t.fig.spec %>%
  set_document(figureScaleMode = "fitPage",
               docTemplate = "Classic_landscape_times")

# --- Figure 2: Iris petal dimensions by species (violin + jitter) ---
# Violin plots show the distribution shape; jittered points show
# individual observations. Legend is turned off because species
# identity is clear from the x-axis labels.
t.fig2 <- ggplot(iris, aes(x = Species, y = Petal.Length, fill = Species)) +
  geom_violin(alpha = 0.4, colour = NA) +
  geom_jitter(aes(colour = Species), width = 0.15, size = 1.5, alpha = 0.7) +
  scale_fill_manual(values = c("setosa" = "#66C2A5", "versicolor" = "#FC8D62",
                                "virginica" = "#8DA0CB")) +
  scale_colour_manual(values = c("setosa" = "#66C2A5", "versicolor" = "#FC8D62",
                                  "virginica" = "#8DA0CB")) +
  labs(x = NULL, y = "Petal Length (cm)") +
  theme_minimal(base_size = 11) +
  theme(legend.position = "none")

t.fig.spec2 <- t.fig2 %>% create_figure() %>%
  add_title(
    c("Study Iris",
      "Figure 2: Petal Length Distribution by Species"),
    toclevel = 1
  ) %>%
  add_subtitle("Anderson's Iris data set (n = 150)") |>
  add_footnote(
    "Each point represents one flower. Violin width shows density."
  ) %>%
  set_document(figureScaleMode = "fitPage",
               docTemplate = "Classic_landscape_times")

# --- Figure 3: Displacement vs horsepower (bubble + LOESS smooth) ---
# Bubble size encodes quarter-mile time; fill colour encodes transmission
# type (automatic vs manual). A LOESS curve with 95% CI ribbon shows
# the overall trend.
t.fig3 <- ggplot(mtcars, aes(x = disp, y = hp)) +
  geom_smooth(method = "loess", formula = y ~ x,
              se = TRUE, colour = "#B2182B", fill = "#FDDBC7", alpha = 0.3) +
  geom_point(aes(size = qsec, fill = factor(am)),
             shape = 21, alpha = 0.75, colour = "grey30") +
  scale_fill_manual(name = "Transmission",
                    values = c("0" = "#4393C3", "1" = "#D6604D"),
                    labels = c("0" = "Automatic", "1" = "Manual")) +
  scale_size_continuous(name = "1/4 Mile Time (s)", range = c(2, 8)) +
  labs(x = "Displacement (cu. in.)", y = "Horsepower") +
  theme_bw(base_size = 11) +
  theme(legend.position = "bottom",
        legend.box = "vertical",
        legend.margin = margin(t = 2, b = 2),
        legend.spacing.y = unit(2, "pt"))

t.fig.spec3 <- t.fig3 %>% create_figure() %>%
  add_title(c("Study Motor Trend",
              "Figure 3: Displacement vs Horsepower"), toclevel = 1) %>%
  add_subtitle("Bubble size = quarter-mile time; colour = transmission type") |>
  add_footnote(
    paste("LOESS curve with 95% CI shown in red.",
          "Source: 1974 Motor Trend US magazine.")
  ) %>%
  set_document(figureScaleMode = "fitPage",
               docTemplate = "Classic_landscape_times")

# --- Combine all three figures into a single document ---
# create_report() accepts any number of TFL_spec objects.
# write_doc() with toc = TRUE generates a Table of Contents from
# the toclevel values set in each spec's title.
t.fig.report <- create_report(t.fig.spec, t.fig.spec2, t.fig.spec3)

write_doc(t.fig.report, "example_05_figures_single_doc_toc", toc = TRUE)

p <- ggplot2::ggplot(pk, ggplot2::aes(TIME, CONC, colour = TRT, shape = TRT)) +
    ggplot2::geom_line(linewidth = 0.9) +
    ggplot2::geom_point(size = 2.8) +
    ggplot2::scale_x_continuous(breaks = c(0, 0.5, 1, 2, 4, 8, 12)) +
    ggplot2::labs(x = "Time (h)", y = "Concentration (ng/mL)") +
    ggplot2::theme_bw(base_size = 11) +
    ggplot2::theme(legend.position = "bottom")

spec_fig <- create_figure(p) %>%
    add_title(c("Figure S3.1", "Mean PK Concentration–Time Profile"), toclevel = 1) %>%
    add_subtitle("PK Analysis Set") %>%
    set_document(continuousSection = TRUE, figureHeight = '3in')

spec_tbl <- create_table(summary_tbl) %>%
  define_cols(TRT, label = "Treatment", isID = TRUE, colWidth = "40%") %>%
  define_cols(Cmax, label = "C[max]", type = "numeric", format = "%.1f", valueStyleRef = "text_center") %>%
  define_cols(Tmax, label = "T[max] (h)", type = "numeric", format = "%.1f", valueStyleRef = "text_center") %>%
  add_footnote("C[max] = maximum concentration; T[max] = time of C[max].") %>%
  set_document(continuousSection = TRUE)

create_report(spec_fig, spec_tbl) %>%
  write_doc("table_under_figure", toc = TRUE)

spec_tbl_titled <- create_table(summary_tbl) %>%
  add_title(c("Table S3.1", "PK Summary Parameters"), toclevel = 1) %>%
  define_cols(TRT, label = "Treatment", isID = TRUE, colWidth = "40%") %>%
  define_cols(Cmax, label = "C[max]", type = "numeric", format = "%.1f", valueStyleRef = "text_center") %>%
  define_cols(Tmax, label = "T[max] (h)", type = "numeric", format = "%.1f", valueStyleRef = "text_center") %>%
  add_footnote("C[max] = maximum concentration; T[max] = time of C[max].") %>%
  set_document(continuousSection = TRUE)

create_report(spec_fig, spec_tbl_titled) %>%
  write_doc("table_under_figure_titled", toc = TRUE)

spec_fig_compact <- create_figure(p) %>%
    add_title(c("Figure S3.1", "Mean PK Concentration–Time Profile"), toclevel = 1) %>%
    add_subtitle("PK Analysis Set") %>%
    # Reduce from 3in to 2in to leave more room for the table on the same page
    set_document(continuousSection = TRUE, figureHeight = '2in')

create_report(spec_fig_compact, spec_tbl) %>%
  write_doc("table_under_figure_compact", toc = TRUE)