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pwranova is an R package for power analysis in ANOVA
designs, including between-, within-, and mixed-factor designs, with
full support for both main effects and interactions across any
number of factors.
The package allows calculation of statistical power, required total sample size, significance level, and minimal detectable effect sizes expressed as partial eta squared or Cohen’s f for ANOVA terms and planned contrasts. In addition, complementary functions are included for common related tests such as t-tests and correlation tests, making the package a convenient toolkit for power analysis in experimental psychology and related fields.
You can install pwranova from GitHub using
devtools:
# Install devtools if not already installed
if (!requireNamespace("devtools", quietly = TRUE)) {
install.packages("devtools")
}
# Install pwranova
devtools::install_github("mutopsy/pwranova")No heavy external dependencies are required for the core functionality.
library(pwranova)
### 1) Compute power (given N, effect size, alpha)
# One between factor (3 levels), no within factor
res_power_between <- pwranova(
nlevels_b = 3,
n_total = 60,
cohensf = 0.25,
alpha = 0.05
)
res_power_between
# One within factor (4 levels), no between factor
# (Optionally set epsilon for sphericity correction; default is 1)
res_power_within <- pwranova(
nlevels_w = 4,
n_total = 30,
cohensf = 0.50,
alpha = 0.05,
epsilon = 1.00
)
res_power_within
# Mixed design: one between factor (2 levels) and two within factors (2 and 3 levels)
# Show only a selected term with `target` if you want a compact output
res_power_mixed <- pwranova(
nlevels_b = 2,
nlevels_w = c(2, 3),
n_total = 30,
cohensf = 0.50,
alpha = 0.05,
epsilon = 1.00,
target = "B1:W2" # show only 2x3 interaction of the between factor and the second within factor
)
res_power_mixed
### 2) Solve required total N (given target power)
# One between factor (3 levels), no within factor
res_n_between <- pwranova(
nlevels_b = 3,
cohensf = 0.25,
alpha = 0.05,
power = 0.80
)
res_n_between # returns the smallest total N (multiple of groups) meeting the target power
### 3) Planned contrast power
# Contrast weights must sum to 0
res_contrast <- pwrcontrast(
weight = c(1, -1, 0), # three conditions, compare 1 vs 2
paired = FALSE,
n_total = 60,
cohensf = 0.25,
alpha = 0.05
)
res_contrastCurrent functions include:
pwranova() — Power analysis for
between-/within-/mixed-factor ANOVA, covering all main effects and
interactions.pwrcontrast() — Power analysis for a single planned
contrast (1 df) in between-subjects or paired/repeated-measures
designs.pwrttest() — Power analysis for t-tests
(one-sample, paired, and two-sample).pwrcortest() — Power analysis for Pearson’s correlation
(using either the t-distribution or Fisher’s
z-transformation approach).For full documentation, see the reference site (pkgdown): https://mutopsy.github.io/pwranova/reference/
Please cite the following preprint when using this package:
Muto, H. (2025). pwranova: An R package for power analysis of flexible ANOVA designs and related tests. Jxiv. https://doi.org/10.51094/jxiv.1555
See the Changelog: https://mutopsy.github.io/pwranova/news/
GPL-3
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.