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.
Create publication-ready statistical tables for reports and manuscripts.
| 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 |
Expected: A table package selected based on the output format and use case. The chosen package is installed and loadable.
On failure: If the required package is not installed, run install.packages("gt") (or the appropriate package). For gtsummary, both gt and gtsummary must be installed.
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*")
)
Expected: A gt table object with formatted means, SDs, and counts grouped by category. Column headers use proper statistical notation (italicized M, SD, n).
On failure: 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.
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")
Expected: A gtsummary regression table with bolded p-values, model fit statistics (R-squared, N) in a source note, and a descriptive caption.
On failure: 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).
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")
Expected: A lower-triangle correlation matrix rendered as a gt table with blanked upper triangle, two decimal places, and a clear caption.
On failure: 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.
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")
Expected: 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.
On failure: 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().
# 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")
Expected: Table saved to the specified file format (HTML, Word, PNG, or PDF). The output file opens correctly in the appropriate application.
On failure: 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.
```{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.
Expected: 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.
On failure: 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.
fmt_number() (gt) or format() rather than round() for displaysub_missing() in gt or options(knitr.kable.NA = "")landscape() or font size reductionformat-apa-report - tables within APA manuscriptscreate-quarto-report - embedding tables in reportsbuild-parameterized-report - tables that adapt to parametersnpx skills add pjt222/generate-statistical-tables下载完整 Skill 目录，包含 SKILL.md 及所有相关文件
Category:science-education