---

name: generate-statistical-tables locale: caveman-ultra source_locale: en source_commit: 82c77053 fence_basis_commit: 82c77053 translator: "Julius Brussee homage — caveman" translation_date: "2026-04-24" description: > Generate publication-ready statistical tables using gt, kableExtra, or flextable. Covers descriptive statistics, regression results, ANOVA tables, correlation matrices, and APA formatting. Use when creating descriptive statistics tables, formatting regression or ANOVA output, building correlation matrices, producing APA-style tables for academic papers, or generating tables for Quarto and R Markdown documents. license: MIT allowed-tools: Read Write Edit Bash Grep Glob metadata: author: Philipp Thoss version: "1.0" domain: reporting complexity: intermediate language: R tags: r, tables, gt, statistics, publication

Generate Statistical Tables

Pub-ready stat tables for reports + manuscripts.

Use When

• Descriptive stats tables
• Regression / ANOVA output format
• Correlation matrices
• APA-style academic
• Quarto / R Markdown tables

In

• Required: stat results (models, summaries)
• Required: out format (HTML, PDF, Word)
• Optional: style guide (APA, journal)
• Optional: numbering scheme

Do

Step 1: Choose pkg

Package	Best for	Formats
gt	HTML, general-purpose	HTML, PDF, Word
kableExtra	LaTeX/PDF documents	PDF, HTML
flextable	Word documents	Word, PDF, HTML
gtsummary	Clinical/statistical summaries	All via gt/flextable

→ Pkg selected by format + use case, installed + loadable.

If err: missing → install.packages("gt") (or proper). gtsummary needs gt + gtsummary.

Step 2: Descriptive stats

library(gt)

descriptives <- data |>
  group_by(group) |>
  summarise(
    n = n(),
    M = mean(score, na.rm = TRUE),
    SD = sd(score, na.rm = TRUE),
    Min = min(score, na.rm = TRUE),
    Max = max(score, na.rm = TRUE)
  )

gt(descriptives) |>
  tab_header(
    title = "Table 1",
    subtitle = "Descriptive Statistics by Group"
  ) |>
  fmt_number(columns = c(M, SD), decimals = 2) |>
  fmt_number(columns = c(Min, Max), decimals = 1) |>
  cols_label(
    group = "Group",
    n = md("*n*"),
    M = md("*M*"),
    SD = md("*SD*")
  )

→ gt object w/ M, SD, n grouped, italic headers.

If err: group_by() unexpected → verify var + levels. fmt_number() err → numeric cols.

Step 3: Regression results

model <- lm(outcome ~ predictor1 + predictor2 + predictor3, data = data)

library(gtsummary)

tbl_regression(model) |>
  bold_p() |>
  add_glance_source_note(
    include = c(r.squared, adj.r.squared, nobs)
  ) |>
  modify_header(label = "**Predictor**") |>
  modify_caption("Table 2: Regression Results")

→ Regression table w/ bold p, fit stats note, caption.

If err: tbl_regression() fail → verify model obj (lm, glm). add_glance_source_note() err → check broom::glance(model).

Step 4: Correlation matrix

library(gt)

cor_matrix <- cor(data[, c("var1", "var2", "var3", "var4")],
                  use = "pairwise.complete.obs")

# Format lower triangle
cor_matrix[upper.tri(cor_matrix)] <- NA

as.data.frame(cor_matrix) |>
  tibble::rownames_to_column("Variable") |>
  gt() |>
  fmt_number(decimals = 2) |>
  sub_missing(missing_text = "") |>
  tab_header(title = "Table 3", subtitle = "Correlation Matrix")

→ Lower-triangle cor matrix w/ blanked upper, 2 dec, caption.

If err: sub_missing() not blanking → check NA set. Non-numeric → cor() fails → filter numeric.

Step 5: ANOVA table

aov_result <- aov(score ~ group * condition, data = data)

library(gtsummary)

tbl_anova <- broom::tidy(aov_result) |>
  gt() |>
  fmt_number(columns = c(sumsq, meansq, statistic), decimals = 2) |>
  fmt_number(columns = p.value, decimals = 3) |>
  cols_label(
    term = "Source",
    df = md("*df*"),
    sumsq = md("*SS*"),
    meansq = md("*MS*"),
    statistic = md("*F*"),
    p.value = md("*p*")
  ) |>
  tab_header(title = "Table 4", subtitle = "ANOVA Results")

→ ANOVA w/ Source, df, SS, MS, F, p. Interactions labeled, p to 3 dec.

If err: broom::tidy(aov_result) unexpected cols → verify aov obj. Type III SS → car::Anova(model, type = 3).

Step 6: Save

# Save as HTML
gtsave(my_table, "table1.html")

# Save as Word
gtsave(my_table, "table1.docx")

# Save as PNG image
gtsave(my_table, "table1.png")

# For LaTeX/PDF (kableExtra)
kableExtra::save_kable(kable_table, "table1.pdf")

→ Saved to format. Opens correctly.

If err: gtsave() Word fail → install webshot2. PDF via kableExtra → install TinyTeX/MiKTeX.

Step 7: Embed in Quarto

```{r}
#| label: tbl-descriptives
#| tbl-cap: "Descriptive Statistics by Group"

gt(descriptives) |>
  fmt_number(columns = c(M, SD), decimals = 2)
```

See @tbl-descriptives for summary statistics.

→ Renders inline w/ @tbl-* cross-ref + caption. Adapts to format.

If err: no render → chunk label tbl- prefix. PDF formatting lost → switch gt → kableExtra.

Check

• Renders in target format
• Consistent number format
• Stat notation per style (italic, symbols)
• Clear caption + numbering
• Meaningful headers
• Notes/footnotes explain abbrevs + sig markers

Traps

• gt in PDF: limited. Use kableExtra for LaTeX.
• Rounding inconsistency: fmt_number() (gt) / format() not round().
• Missing values: sub_missing() (gt) or options(knitr.kable.NA = "").
• Wide PDF: landscape() or font reduction.
• APA number: no leading zero when ≤1 (p, corr): ".03" not "0.03".

→

• format-apa-report — APA manuscript tables
• create-quarto-report — embed in reports
• build-parameterized-report — param-adaptive tables