generate-statistical-tables

# Generate Statistical Tables

Create publication-ready statistical tables for reports and manuscripts.

## When to Use

- Creating descriptive statistics tables
- Formatting regression or ANOVA output
- Building correlation matrices
- Producing APA-style tables for academic papers
- Generating tables for Quarto/R Markdown documents

## Inputs

- **Required**: Statistical analysis results (model objects, summary data)
- **Required**: Output format (HTML, PDF, Word)
- **Optional**: Style guide (APA, journal-specific)
- **Optional**: Table numbering scheme

## Procedure

### Step 1: Choose Table Package

| 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 |

**Got:** A table package selected based on output format and use case. The chosen package is installed and loadable.

**If fail:** If the required package is not installed, run `install.packages("gt")` (or the appropriate package). For `gtsummary`, both `gt` and `gtsummary` must be installed.

### Step 2: Descriptive Statistics Table

```r
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*")
  )
```

**Got:** A `gt` table object with formatted means, SDs, and counts grouped by category. Column headers use proper statistical notation (italicized *M*, *SD*, *n*).

**If fail:** If `group_by()` produces unexpected results, verify the grouping variable exists and has the expected levels. If `fmt_number()` throws an error, ensure the target columns contain numeric data.

### Step 3: Regression Results Table

```r
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")
```

**Got:** A `gtsummary` regression table with bolded p-values, model fit statistics (R-squared, N) in a source note, and a descriptive caption.

**If fail:** If `tbl_regression()` fails, verify the input is a model object (e.g., `lm`, `glm`). If `add_glance_source_note()` errors, check that `broom` can tidy the model: `broom::glance(model)`.

### Step 4: Correlation Matrix

```r
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")
```

**Got:** A lower-triangle correlation matrix rendered as a `gt` table with blanked upper triangle, two decimal places, and a clear caption.

**If fail:** If `sub_missing()` does not blank the upper triangle, verify that `NA` values were set correctly with `cor_matrix[upper.tri(cor_matrix)] <- NA`. If variables are non-numeric, `cor()` will fail; filter to numeric columns first.

### Step 5: ANOVA Table

```r
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")
```

**Got:** A formatted ANOVA table with Source, *df*, *SS*, *MS*, *F*, and *p* columns. Interaction terms are clearly labeled and p-values are formatted to three decimal places.

**If fail:** If `broom::tidy(aov_result)` produces unexpected columns, verify the model is an `aov` object. For Type III sums of squares, use `car::Anova(model, type = 3)` instead of base `aov()`.

### Step 6: Save Tables

```r
# 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")
```

**Got:** Table saved to the specified file format (HTML, Word, PNG, or PDF). The output file opens correctly in the appropriate application.

**If fail:** If `gtsave()` fails for Word format, ensure the `webshot2` package is installed. For PDF output via `kableExtra`, ensure a LaTeX distribution (TinyTeX or MiKTeX) is installed.

### Step 7: Embed in Quarto Document

````markdown
```{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.
````

**Got:** The table renders inline in the Quarto document with a cross-referenceable label (`@tbl-*`) and a proper caption. The table adapts to the document's output format automatically.

**If fail:** If the table does not render, verify the chunk label starts with `tbl-` for Quarto cross-referencing. If formatting is lost in PDF, switch from `gt` to `kableExtra` for LaTeX-based output.

## Validation

- [ ] Table renders correctly in target format (HTML, PDF, Word)
- [ ] Numbers are formatted consistently (decimal places, alignment)
- [ ] Statistical notation follows the style guide (italicized, proper symbols)
- [ ] Table has a clear caption and numbering
- [ ] Column headers are meaningful
- [ ] Notes/footnotes explain abbreviations or significance markers

## Pitfalls

- **gt in PDF**: gt has limited PDF support. Use kableExtra for LaTeX-heavy documents.
- **Rounding inconsistency**: Use `fmt_number()` (gt) or `format()` rather than `round()` for display
- **Missing values display**: Configure with `sub_missing()` in gt or `options(knitr.kable.NA = "")`
- **Wide tables in PDF**: Tables exceeding page width need `landscape()` or font size reduction
- **APA number formatting**: No leading zero for values bounded by 1 (p-values, correlations): ".03" not "0.03"

## Related Skills

- `format-apa-report` - tables within APA manuscripts
- `create-quarto-report` - embedding tables in reports
- `build-parameterized-report` - tables that adapt to parameters