statAPA produces publication-ready statistical
tables and figures formatted according to the 7th edition of the
American Psychological Association (APA) style guidelines. Output can be
directed to the R console, Microsoft Word (via officer +
flextable), or LaTeX.
Install the released version from CRAN:
install.packages("statAPA")Or the development version from GitHub:
# install.packages("remotes")
remotes::install_github("causalfragility-lab/statAPA")| Function | What it does |
|---|---|
apa_descriptives() |
Descriptive statistics table (optionally by group) |
apa_t_test() |
One-sample, two-sample (Welch/pooled), and paired t-tests |
apa_z_test_mean() |
z-test with known population standard deviation(s) |
apa_chisq() |
Chi-square test (goodness-of-fit or independence) |
apa_prop_test() |
Proportion test with risk difference, risk ratio, odds ratio |
apa_anova() |
One-way ANOVA/ANCOVA (Type II/III) with effect sizes |
apa_ancova() |
ANCOVA with covariate validation and adjusted means |
apa_twoway_anova() |
Two-way ANOVA with interaction and simple effects |
apa_manova() |
MANOVA (Pillai, Wilks, Hotelling-Lawley, Roy) |
apa_posthoc() |
Post-hoc pairwise comparisons (emmeans) |
apa_table() |
Regression / multilevel coefficient table |
apa_robust() |
Robust regression (HC or cluster-robust SEs) |
apa_hetero() |
Heteroscedasticity diagnostics |
apa_homoskedasticity() |
Homoskedasticity check (Breusch-Pagan, White, Levene) |
apa_multilevel() |
Multilevel models: fixed/random effects, ICC, R², model comparison |
apa_plot_descriptives() |
Mean ± 95% CI plot by group |
apa_plot_regression() |
Fitted-line plot with confidence ribbon |
apa_plot_anova() |
Estimated marginal means plot |
apa_plot_residuals() |
Residual diagnostic plots |
apa_to_flextable() |
Convert any result to an APA-styled flextable |
save_apa() |
Save a ggplot figure at 300 dpi with APA dimensions |
theme_apa() |
APA-style ggplot2 theme |
library(statAPA)
# Descriptive statistics
apa_descriptives(mtcars, vars = c("mpg", "wt", "hp"), group = "cyl")
# t-test
apa_t_test(mtcars$mpg[mtcars$am == 0],
mtcars$mpg[mtcars$am == 1],
output = "console")
# Two-way ANOVA with simple effects
mtcars2 <- transform(mtcars, cyl = factor(cyl), gear = factor(gear))
apa_twoway_anova(mpg ~ cyl * gear, data = mtcars2,
factorA = "cyl", factorB = "gear")
# MANOVA
apa_manova(cbind(Sepal.Length, Petal.Length) ~ Species, data = iris)
# Multilevel model
library(lme4)
data(ECLS_demo)
m0 <- lmer(math ~ 1 + (1 | schid), data = ECLS_demo, REML = FALSE)
m1 <- lmer(math ~ SES + (1 | schid), data = ECLS_demo, REML = FALSE)
apa_multilevel(m0, m1, model_names = c("Null", "+ SES"))
# Export to Word
fit <- lm(mpg ~ wt + hp, data = mtcars)
apa_table(fit, output = "word", file = "regression_table.docx")If you use statAPA in published research, please cite: Hait, S. (2026). statAPA: APA 7th Edition Statistical Tables, Plots, and Multilevel Model Reports. R package version 0.1.0. https://CRAN.R-project.org/package=statAPA —
MIT © 2026 Subir Hait