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statAPA

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.

Installation

Install the released version from CRAN:

install.packages("statAPA")

Or the development version from GitHub:

# install.packages("remotes")
remotes::install_github("causalfragility-lab/statAPA")

Functions at a glance

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

Quick example

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")

Citation

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 —

License

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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