pyWebpower

A Python implementation of the WebPower R package — a library for calculating statistical power, sample size, and minimum detectable effect for a wide range of statistical tests.

This is a collection of tools for conducting both basic and advanced statistical power analysis including correlation, proportion, t-test, one-way ANOVA, two-way ANOVA, linear regression, logistic regression, Poisson regression, mediation analysis, longitudinal data analysis, structural equation modeling and multilevel modeling.

Installation

pip install pywebpower

Quick Start

Leave exactly one parameter as None — that is the quantity to be solved for.

from webpower.power_tests import wp_anova_test

# Solve for power
result = wp_anova_test(f=0.25, k=4, n=100, alpha=0.05)
print(round(result["power"], 4))  # 0.5182

# Solve for required sample size
result = wp_anova_test(f=0.25, k=4, n=None, alpha=0.05, power=0.8)
print(result["n"])  # 179

Available Tests

Function	Description
wp_anova_test	One-way ANOVA
wp_anova_binary_test	One-way ANOVA with binary outcome
wp_anova_count_test	One-way ANOVA with count outcome
wp_kanova_test	Multi-way ANOVA
wp_rmanova_test	Repeated-measures ANOVA
wp_t1_test	One-sample / paired / two-sample t-test
wp_t2_test	Unbalanced two-sample t-test
wp_one_prop_test	One-sample proportion test
wp_two_prop_one_n_test	Two-sample proportion test (equal n)
wp_two_prop_two_n_test	Two-sample proportion test (unequal n)
wp_regression_test	Multiple linear regression
wp_poisson_test	Poisson regression
wp_logistic_test	Logistic regression
wp_mediation_test	Simple mediation analysis
wp_correlation_test	Correlation
wp_sem_chisq_test	SEM (Satorra & Saris chi-square method)
wp_sem_rmsea_test	SEM (RMSEA-based)
wp_mrt2arm_test	Multisite randomised trial — 2 arms
wp_mrt3arm_test	Multisite randomised trial — 3 arms
wp_crt2arm_test	Cluster randomised trial — 2 arms
wp_crt3arm_test	Cluster randomised trial — 3 arms

Requirements

• Python 3.10+
• NumPy
• SciPy

Contributing

See CONTRIBUTING.md.

License

MIT

References

Zhang, Z., & Yuan, K.-H. (2018). Practical Statistical Power Analysis Using Webpower and R. ISDSA Press.